Original Post

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

In this blog post I want to talk about who are my prospective clients.

If you fit into one of these categories you might want to check out my freebies.

Given the fact that I have taken the public position that women criminals should get the same jail time as men criminals?

It is very obvious that my prospective clients are exclusively men.

Even so. Not all men believe that women criminals should get the same jail time as men criminals.

If you are a man and you are ok with women committing crimes against your fellow men?

Then I suggest you simply move along, because you and I are not going to get along in business.

I only want men as my clients who take the position, even if privately, that women criminals should get the same jail time as men criminals.

Of course, on the other hand all women take the position that women should be able to commit crimes against men with impunity.

For this reason women are not my prospective clients.

Similarly, because all women support women’s crimes against men, those men who may become my prospective clients are well advised to keep their relationship with me a secret from any woman in their life.

Personally, I think that it is sad that men must do business with me in secret.

But women will do everything they can to destroy the life of any man who is known to be one of my clients.

Given this restriction on my ability to do business?

Then who are my prospective clients?

One.

The man most likely to become one of my clients is the very highly intelligent business analyst who works for a large company.

His job is to analyze company data in order to come up with new ideas in order to improve the profitability of his company’s business.

What are the motivations for a very highly intelligent business analyst to become one of my clients?

This man will be seeking promotions and pay rises in his company to climb the corporate ladder.

This man will be seeking to learn as much as possible about how to sustainably increase the profitability of his organization, so as to win those promotions and pay rises on merit, inside his company.

This man will also be very keen to learn about his industry segment, so if he is not awarded the pay rises and promotions he feels he has earned, he can easily go to another company, or start his own consulting business in his segment.

If you are a very high IQ man in a mass market consumer company who has the role of coming up with new ideas to increase the profitability of your company?

Then you are very much the sort of man I would like to talk with.

My credentials in this area include being hired by the richest man in Australia to make an attempt to turn around one of his companies that was in long term decline.

I was also the man who gave the National Australia Bank the ideas they needed to double their profit over a five year period.

I am very expert in how to increase profitability in such segments as telco, retail, insurance and similar areas.

Many of my clients have managed to double their company profit by taking my advice.

If you are in the position to write business cases for new proposals in your company, that are intended to increase the profitability of your company?

Then you may well like to have me as your confidential advisor.

Two.

The second group of men who may want to become my client can be described as follows.

You own your own data warehousing company and you would like to increase the profitability of your company.

If you would like an example of the sort of company I am talking about?

Then I will put the link for Key Work Consulting below.

Key Work

The background to Key Work Consulting is as follows.

I met the co-owner of Key Work Consulting in 1999.

His name is Tobin Wotring and we met on the D W list forum.

Tobin asked if I would be willing to help him get his new company started and he did not have any spare cash to pay me.

I agreed to help him out, and later he became a very good client of mine.

Still later he saved my life.

So making a great friend who later saves your life is a really good thing to have happened just for giving him some free advice on how to get his company going.

Tobin Wotring bought my E T L software in 2007 and hired me to train his senior staff.

As a result of being my client he was able to significantly increase the profitability of his business.

In fact Tobin had the opportunity to make a sales pitch to Zurich insurance in Zurich Switzerland. I gave him many pointers on how to go through that sales cycle. I was able to do that because I had many years of insurance experience.

The result was that Tobin won Zurich Insurance as a very large client for his company. Tobin himself would say that he would never have won the Zurich Insurance deal without my advice.

Of course the success of Key Work Consulting was not entirely my doing, they had excellent staff who were great at their jobs. They just needed some training on how to do things better than they knew.

It is a matter of public record that I played a significant role in making them one of the leading data warehousing consulting companies in Germany.

Today Key Work Consulting is exclusively owned by Tobin Wotring’s ex-wife Petra.

This is why I can mention my time there because no women are going to attack a company wholly owned by a woman. Especially not a woman who stole millions of euros from her husband. Women will applaud that woman.

If you are a man who owns his own data warehousing company?

Then you can check out Key Work Consulting and see the success that one of my best clients ever had. I can give you the names of former employees. You can go and talk to them in order to understand my role in helping Tobin Wotring, and his co-owner, create one of the most successful data warehousing companies in Germany.

In order for you not to be sabotaged by the women in your company you would engage me via a third party.

I have a number of business partners who are fathers of boys who understand why I have taken the positions I have.

They are willing to take on clients and to keep my name out of the mix.

I have trained the staff of these business partners and they have access to all my intellectual property.

If you are also willing to take the risk of speaking to me directly? Then that is up to you.

If you are a Muslim business owner and you operate in an area where the women in your company will not sabotage you company?

Then you are welcome to do business with me directly if you would like.

At the end of the day?

There are two very successful data warehousing consulting companies that I greatly helped along the way.

I am using Key Work Consulting as the example because it is the best example of the two and it is well known that they were my client for many years. The other one is not so well known to be linked to me and they did not adopt my software.

Three.

The third man who may wish to become my client is the man who is a world class data modeler and data warehouse architect.

This man may work for his own company as a sole business owner, or this man may have a data warehousing company of his own with his own employees similar to the situation of number one above.

The reason this man may be interested in becoming my client is the idea of mega models.

If you are a world class dimensional data modeler the opportunity for you is to develop your own mega model that you will then sell out on the open market.

If you are a world class dimensional data modeler you can click on the buttons below and go and read about what I have called mega models.

IBI053-Blog Post

IBI054-Blog Post

IBI065-Blog Post

If you have read the blog posts linked above? You will immediately understand the potential business opportunity for you.

Then the question for you becomes whether you want to make the investment into developing a mega model.

If you only want to perform the development work and do not wish to try and engage in global sales of your mega model?

Then I have business partners who would be interested in discussing the resale of your mega model for an appropriate commission.

In this case you could remain a solo business owner and yet still have the business opportunity to sell your mega model world wide through a business partner that can provide 24 by 7 support for production installations.

This is the best of both worlds for you, because you can spend 100% of your time focused on building the mega model for the large operational system you know very well, without having to support the sales effort or support the production installations.

In this case you would become my client in order to understand how to build your mega model and how to populate it using my ETL software. That means only you need to know that you are talking to me.

To complete this blog post.

There are other men who would benefit from being my client and learning how to become a world class data warehouse architect using my training materials.

All those training materials are published in my freebies.

Any man who wants to learn from my 35 years of experience in the data warehousing area is welcome to download all my freebies and get cracking.

The men who do that can then just pay me my advertised rates for one on one discussions and for answering one on one private questions.

I would like to make it very clear that I am not interested in running any type of training or school style business in my data warehousing business. My business is not a training business for just any man who wants to do data warehousing.

My business is working with already well established, very high IQ men, to improve the profitability of the business they are already in or already own.

We have seen the results of Ralph Kimball’s efforts to establish Kimball University.

I would like to just do a side bar on this comment if you are willing to read this.

Ralph did his very best to run training for large numbers of students coming into data warehousing at the entry level.

Those results are not particularly encouraging.

What we got out of Kimball University were thousands and thousands of men who learned the very basics and who then implemented bad data warehouses. Those men who implemented bad data warehouses did the rest of us no favours. The reputation of Data Warehousing has been very badly tarnished by those men.

Ralph is a good friend of mine. I know that in training men he had his heart in the right place. He sincerely wanted men to learn how to implement dimensional models very well so as to improve the performance of their businesses. But his students, for the most part, went on to create disasters that then reflected on us all.

As a result? I am not interested in teaching men who will only go on to do poor work that reflects badly on me. I will leave that nonsense to the self described data leaders like Joe Reese.

I have business partners who have very well trained staff who can take over the running of any existing data warehouse and provide 24 by 7 support.

With the acceptance of cloud computing and the acceptance of off site support?

It no longer makes business sense to have men who are lacking interest and excellence to provide support for data warehouses just because they sit at a desk inside your companies four walls.

It also makes no sense to have men who are sitting else where to make a mess of your data warehouse just because they are cheap. Poorly trained men making a mess of your data warehouse have costs to your business far in excess of the cheap daily rate they are charging you.

All companies now have the ability to have my well trained business partners look after their data warehouses.

Any company can create V P N access to their on premise data warehouse.

Any company can provide V P N access to their cloud based data warehouse.

The days of getting poorly qualified, poorly motivated, men or women, to support your data warehouse just because they sit inside your offices or just because they are cheap are over.

You can get the very best of men, very well trained, very motivated, to support your data warehouse for costs that might just surprise you.

You can talk to me directly for more information if you like.

So. To be clear.

I would very much prefer to work with the very best of men in our industry segment who have already established their credentials.

Between Bill Inmon, Ralph Kimball, and myself?

We have published everything needed for a bright young man to make his way into the data warehousing area without any more free help from me.

I even have a blog post on how to become great in your profession and I will put it on a button below.

Your Profession

I do have other areas of business I am working in.

However, these areas of business are not being related to me publicly.

Those men who become my clients and earn my trust may be informed of these other areas of business in the fullness of time.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

Post script.

If you like my blog posts and would like to help me replace some of the five million dollars it has cost me to save men’s lives and defend the rights of men and boys?

Please buy me a coffee on my buy me a coffee link.

As at the time of writing I have about two hundred and thirty thousand dollars in debt for being willing to risk my life to defend those less able to defend themselves.

Thank you in advance for those of you who buy me a coffee.

It is much appreciated.

Buy Me A Coffee

Share

Original Post

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

As I have recently announced on my channel.

I will be doing some opinion pieces and response videos.

In this blog post I want to talk about the two edged sword of speaking in public.

So.

On with the blog post.

The algorithms for all these social media sites reward frequency of posting.

This means that they want you to come to their site every day and post something. They want you to say something out in the public so that they can push your post out in front of other people who are also on their social media platform.

You can understand that’s their business.

That’s what they want to do.

Their business is to get as many people as possible looking at their site for as long as possible, every day.

That’s their business, right?

They set their algorithms up so you are rewarded if you post frequently.

There is a 2 edged sword to this because guess what?

If you decide to post frequently, what is it you are going to say?

What are you going to say every day that has any value at all?

Well, not much.

You are not going to say much that has any value at all every day.

In fact, the things that you say that have value take a long time to write.

Because they take a long time to write, you post them infrequently.

So one of the pieces of the double edged sword of talking in public, particularly on social media sites, is when you post, the social media sites?

They encourage you to post frequently,

But when you post? You are not saying much and that degrades the quality of your posting and people are less interested.

In order to overcome that?

What did people do?

They posted click bait.

They posted rage bait because people are never sick of being enraged.

People are very happy to be enraged by something and they will respond to a comment that enrages them.

This is why, on all the social media sites, you see so much rage bait.

This is why the social discourse has turned into one of rage bait.

That is one of the things that is at issue with posting in the public square.

You are tempted by the algorithm to post regularly, and then you post tripe and soon people don’t listen to you.

In order to get people to listen to you then you switch to rage bait.

And here we are.

However, it’s not the biggest issue.

The biggest issue in posting in the public square is this.

Men who know much more about what you are posting will see your posts.

Those men who know much more about what it is you are posting will judge you based on what it is that you say in the public square.

Because they are generally older than you, wiser than you, and much more knowledgeable in your subject than you are?

Their judgement counts, particularly if they decide to make a reply in the public square to your post.

For younger men trying to make it in whatever profession they’re trying to make it in, and I’ll stick to data warehousing and business intelligence, the data area.

Those young men who go out into the public and start posting stuff, make it very clear what it is they know and what it is they don’t know.

To the older men in their segment like me, no amount of tom foolery in your post is going to deceive a man like me in the data area.

Young men posting in the data area are faced with a difficult proposition.

That proposition is you want to make yourself look as knowledgeable as possible.

However, the older, more experienced men in your industry segment can see right through you when you say something, when you talk about something, that you don’t really know about.

This means you have to walk the tightrope of wanting to seem as intelligent as possible but know that there are men who are going to read your posts who will see through you overstating your capabilities.

Your problem is they might just do so.

I, for one, am doing so because I am sick and tired of ignorant young men tarring me with their ignorant brush.

This leaves you as a younger man in a very difficult position.

I would argue sadly so.

What is my advice to young men posting in the public trying to present themselves as marketable?

My advice to you would be this.

Be honest.

Don’t try and oversell yourself.

Don’t try and talk about things that you don’t know anything about.

Just be honest.

Sadly, honesty from young men posting in the public square today is, shall we say, lacking.

For young men posting in the public square, in the data space, my suggestion would be to be honest.

Talk about what you can do and talk about what you can’t do.

Why?

Because the men like me who are hiring managers who might hire you one day?

They will go and look at your statements in the public.

They will know much more about the subject you’re talking about than you.

If you are dishonest in those efforts?

Then, they won’t hire you.

That is how this works.

Not overselling yourself, not overstating yourself in the public square, is a better way of being successful in your chosen profession.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

Post script.

If you like my blog posts and would like to help me replace some of the five million dollars it has cost me to save men’s lives and defend the rights of men and boys?

Please buy me a coffee on my buy me a coffee link.

As at the time of writing I have about two hundred and thirty thousand dollars in debt for being willing to risk my life to defend those less able to defend themselves.

Thank you in advance for those of you who buy me a coffee.

It is much appreciated.

Buy Me A Coffee

Share

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

As I have recently announced on my channel.

I will be doing some opinion pieces and response videos.

In this blog post I want to talk about the term data leader that has been so casually thrown about of late.

Then I want to present a rebuttal to the term data leader with a term that has been around for at least two and a half thousand years and possibly longer.

So.

What is a data leader?

Personally? I have no clue what a data leader is.

I see all these people putting on their profiles that they are a data leader. I see all these people talking about other people and calling them data leaders. But I have no clue what a data leader is. I guess I have only been in this business for forty four years now and I am yet to learn of such things. Or, it could be that the term data leader is as bogus as the term data engineer that we have been hearing so much about lately.

I have already done a post on data engineering and you can go and read it on the button below if you want to.

Data Engineering

I have read books by so called data leaders like Joe Reise and I still have no clue what a data leader is.

So.

My answer to the question, what is a data leader, is that I have no clue what that is.

Here is an idea I was introduced to as a small boy.

When I was five years old, I saw man land on the moon on the television in my kindergarten class.

As you can imagine all us little boys were so excited at this, and we all immediately decided we wanted to be astronauts instead of cowboys. Us little boys asked our teacher what this was all about and how this could be possible.

Our teacher told us that there were some very smart people who worked at a place called NASA, and they were the people who put the two men on the moon that day. I immediately decided I was going to go and work at NASA one day.

Just as a prelude to later comments. I did go and work at NASA in July 1990.

Just twenty one years after I sat there as a starry eyed little boy watching man walk on the moon for the first time?

I was at NASA in Houston with the task of trying to figure out if I could increase the productivity of the eight hundred I B M programmers working on the International Space Station project.

More on that later.

The idea that I was introduced to was the idea of a thought leader.

Someone who thinks of things that no one else around them has thought of.

Once that idea had been presented to me I saw it everywhere men were working.

From the time I was six I used to watch my uncle, who was a builder, work on the houses he was building.

When I was seven I was allowed onto the building sites themselves, to carry tools to and from the trucks of the builders on to the site. I would watch the builders work out a problem that was unexpected with a good new idea.

Of course, builders were coming up with good ideas on each building site because they did not know each other and had no way of easy direct communication.

But the idea was that the builders competed with each other for coming up with good ideas to building problems, and they called this being a “thought leader”.

This was because it took careful thinking to come up with the solutions to these problems.

My uncle taught me that no matter how many houses he had built there were always new problems coming up with each house because each house was unique. He taught me that to build a house your needed to be a good thinker and a good problem solver.

Many years later, in nineteen eighty six, I started work at I B M. I was immediately given access to forums for the I B M software labs where I could see men talking about the problems with I B M software and how to solve them.

One of the men I saw talking was a man named Ueli Wahli. Ueli Wahli was famous in I B M for inventing a way to create overhead slides that had been adopted world wide in I B M. He helped make I B M billions of dollars because his software was used to create slides to present to prospective and existing customers.

There was a term used for Ueli Wahli that I had never heard before. They called him a global thought leader. Kind of like my uncle figuring out problems on building sites but on a global level. We were all in awe of Ueli Wahli.

The joke used to be that we would cross ourselves as we said his name. We all dreamed that one day we would invent something as consequential as the slide software Ueli Wahli had invented. We all dreamed that one day young men like we were now would talk of us as we talked of Ueli Wahli.

And so, in nineteen eighty six I heard the term global thought leader for the first time and it was a title given to Ueli Wahli.

Of course, before Ueli Wahli there had been many thought leaders. I studied philosophy at university and so I had to read about Aristotle, Socrates, Plato and many others. These were men who were the global thought leaders of their time.

So.

I have no clue what a data leader is. But I certainly know what a global thought leader is.

It is a man who comes up with an idea that has never been thought of before that is useful and becomes widely adopted by those who understand the idea, or even just use the idea without understanding it.

Most of the people I see who call themselves data leaders are nothing of the sort. Indeed when self described data leaders talk or write I see nothing new. I have, literally, seen it all before.

To help you understand what it looks like to be a global thought leader I thought I would give you some examples from my career.

For a man to call himself a global thought leader he must have invented some new ideas that were widely adopted that proved to be of great value. For a man to call himself a data leader it seems he merely needs to reproduce that which is already widely known and pretend like he thought of it himself. And sometimes not even with that pretence.

In many cases men who call themselves data leaders don’t even pretend that they are talking about their own ideas. They just don’t reference the man who thought of the ideas they are talking about and let the reader presume some portion of the ideas are the ideas of the self described data leader.

In nineteen eighty nine I was the system architect for a four million dollar software development project. It was a release upgrade of the I B M internal pricing system for Asia Pacific and the Americas. The Americas was all American countries outside of the US.

I had twelve men working for me and source code control was a problem in the I B M world. On my project this problem was a particularly serious concern because of the nature of the application.

We had a source code control product under internal development so I decided to get a copy and try it out. The technical term for it was that it sucked. To link our main driver program took over an hour. I talked to the lab and asked them if they knew how to fix this and no one had any clue. I asked on the forums and no one had any clue.

Simply put, the product only supported object linking and not never call linking. And no one knew how to make it support never call linking. So one weekend I went into the office with the idea that I wanted to solve the problem of never call linking. And I did. I wrote about five thousand lines of assembler code that weekend to make it work and I reported on it on the Monday. I then improved the code over the next couple of weeks and sent it all back to the lab.

They were most grateful for my ideas. The introduction of never call linking and the way in which I solved that problem made the product a viable product. I asked the lab what their plans were to support all the other I B M source code objects.

In the I B M mainframe world we have a lot of types of code that are custom languages for custom objects. If you don’t know about them there is no point explaining them. But everyone who has worked on I B M mainframes knows what they are. They are M F S and D B D and P S B.

The lab told me they had no plans on supporting these things any time soon because they were having enough problems just trying to support the base languages. For this product to be useful on my project I would have to write the code for all the languages that my project used. So over the next month I worked long nights and weekends to write the assemble code needed to support all the language types I needed. I then sent it all back to the lab who thanked me profusely for helping them.

The net result was that I saved one full time headcount on my project and was able to deploy him to doing more useful work when the source code control system was implemented for our project.

The punchline to that story is that no less than Ueli Wahli himself invited me to the Santa Theresa Lab near silicon valley to come and be one of three co-authors on the definitive book on I B M Source code control. So just four years after I first heard the name Ueli Wahli I was working for the man at his invitation.

That is what Global Thought Leadership looks like. You write some new software that is adopted widely. In this case my code was deployed onto every I B M mainframe in the world that ran the I B M Structured Programming Facility. My code managed the code being deployed into production on tens of thousands of I B M mainframes.

One day, while I was working in the conference room at Uelis lab, the phone in the conference room rang. This was very unusual as no one ever called that number. Why would they? We didn’t give the number to anyone.

So I picked up the phone wondering who it was. I said hello this is Peter Nolan speaking, who is this? It was an I B M friend of mine I had met in Sydney. She worked at our largest I B M customer in Australia, a bank called Westpac. Her name was Carol and she was one of the top people in the world in I B M in the area of software development. She had been sent to Westpac to help improve the productivity of the software developers at Westpac.

Her job was to be sent to the largest I B M customers in the world and do what she could to help them be more productive in software development to make better use of our I B M hardware. She had come to our I B M Australia development lab and given lectures to us on the latest ideas, many of which we adopted.

So, I was very confused. I told Carol it was lovely to hear from her and asked how did she get this number. She said Ueli had given it to her. I asked her to what did I owe the honour of her phone call. She said she had been relocated to Houston Texas and was now an advisor to the eight hundred IBM programmers working on the international space station project.

I was very impressed. You don’t get to be an advisor to an I B M team at NASA for no reason. She then went on to explain that they had many serious issues she was trying to help solve on the project. One of those very serious issues was the source code control. She explained that the space station was going to run on intel microprocessors and all the code had to be written in C or assembler for the microprocessors.

And, of course, source code control of assembler and C targeted for microprocessors was not well defined in our source code control product. That portion of the product was still in alpha testing and that was part of what I was working on in the book. We were literally going back and forth with the lab about how to handle microprocessor developed and targeted code.

Carol asked me if I had any ideas on what they might be able to do. We went back and forth for about two weeks on what their problems were. In the end I said that I felt there was a very good chance that if I could spend a couple of days working in the lab with her and the team we could solve some of these problems.

And so, in the week after the July fourth weekend for nineteen ninety I flew over to Houston to work with Carol on these problems. I only had three days because of other commitments. I actually did this work during annual leave I had planned with my wife Jennifer. So Jennifer came in tow to Houston. We got in late Sunday night and I left the hotel at eight o’clock Monday morning and I didn’t see Jennifer awake again until I got to the hotel about ten in the evening on the Wednesday night.

We worked each day until two or three in the morning and then we were all back in the office at nine to start again. On the final day we felt that we had enough to go on by about six in the evening and we went out to a private dinner with the team to have a small celebration.

The code I designed and partly wrote later was used to manage the source code being deployed on the International Space Station. My code was now not only used world wide. My code had now gone out of this world and into space!

That is what a global thought leader looks like. It looks like someone from NASA calls you and asks you to please help them solve their problems for a project as consequential as the international space station.

Something that is very much lacking from the resumes of men who call themselves data leaders is any talk of any projects of similar nature. Indeed, there is a lack of reference to any projects at all.

My next big invention most people in the data warehousing space would be partly familiar with already.

In April nineteen ninety one I was assigned to implement Ralph Kimballs Data Interpretation System Software into my new I B M customer called the Mutal Life Company or M L C for short. I was a young twenty seven year old I B M systems engineer who had just finished his I B M Marketing School. I had to do the same school as the new entries.

I had never built a data warehouse before. A friend of mine was working on the I B M Information Warehouse project at the same lab in Santa Theresa. So I talked with her and talked to people on her team. They all said to go with third normal form and rely on D B 2 to answer questions. So I did. Those who are old enough to remember nineteen ninety know that third normal form was the gospel. That is just how you built database then.

The only problem was the M L C had a million customers and one point one million in force policies. And a party could play many roles on a policy so the table joining the customer table and policy table had six point four million rows in it.

Since virtually every question was about policy holdings by demographics pretty much every question had to scan all three tables. This took an hour elapsed time and cost four hundred Australian dollars per question. I went back to the lab to ask for any more help and they said this was normal. I asked all the worlds top D B 2 experts about how to improve performance and they all said upgrade the mainframe.

In the documentation for the Data Interpretation System there were references to dimensional models and I wrote to the I B M subsidiary Metaphor Computer Systems and asked for their help. They said that the design and creation of their dimensional models was confidential and would not be shared with I B M systems engineers. If our customer wanted dimensional models they would have to fly a team out to Australia to build it.

I was stuck. I could find no one to tell me how to solve the problem of long running queries on D B 2 to make this sale. The project sponsor had been very clear. They loved that they could answer these questions but four hundred dollars per answer and an hour wait time were not acceptable. We had to do better. Of course Teradata were waiting in the wings trying to sell their database computer.

What did I do? I did what I had been taught. I analysed the problem in order to figure out how to solve it. I went over all the queries that were being asked of the third normal form database.

I noticed that they tended to go from a very high summary level down to identifying just a few thousand customers.

I noticed that there were numeric columns that were common in queries such as premium amounts, premium coverage, number of policies, average policy values, forecast premiums and these sorts of things. Please remember my job as an I B M systems engineer meant I could not be told the purpose of these queries. All I had was the S Q L.

I also noticed that there were fields that were common in the queries that were text based or limited values based. These included the role of the person on the policy, age, sex, marital status, state, city, post code, product types, product groups, product sub types, policy age, policy begin dates rolled up to months, quarters, and years.

Slowly but surely I saw the patterns in the S Q L queries. There were textual fields retrieved in a hierarchy and there were numeric fields retrieved by summarisation. This was the main pattern of the queries. So I invented an idea I called multi level summary tables.

The main query table would contain the merger of all the commonly queried data in to one table. There would be one table that was separate that was six point four million rows and it would contain all the details. Then there would be another table that would contain varying levels of summaries of the detailed table. This table would be partitioned and each level of summary would be in it’s own table space. And the first field of the table would be in integer which would define the summary level. The summary levels would be documented against these integers so that the business users knew what integer to put into the query to ask a question.

Then D B 2 would only scan the tablespace for the partition that the query was against. We put the partitions into cylinders on the thirty three eighty disk drives to reduce head movement during the scan of the partition. So basically every query would scan the partition for the level of data that the query was at.

The results were amazing at the time. It was compared to black magic. Many queries that had taken an hour responded in one second or less. Most queries responded in under three seconds. More than ninety nine percent of queries responded in under ten seconds. A query against the detailed table ran out to about 2 minutes to scan all six point four million rows.

And where the query needed data that was not in this merged table you were still looking at an hour and four hundred dollars. Over time we moved more and more fields into this summary table and reduce the hour long queries to be rare.

Of course, everyone in the data warehousing area today knows this as one big table. The difference to one big table is that this is a multi level one big table. The other difference is that I am talking about nineteen ninety one.

Now the caveat here is that Ralph Kimball had invented multi level summary tables in dimensional models independently of me and before me. But since I did not have access to how that was done I had to go for one big table.

In nineteen ninety two I B M got permission from M L C for me to do a speaking tour on what I had done. The actual slide deck had to be approved by the M L C. What I was allowed to say also had to be approved by the M L C.

Over the next 8 years my idea of the multi level summary table was widely implemented in Australia.

That is what global thought leadership looks like. Those are the stories global thought leaders can tell about their past efforts.

In September nineteen ninety three I attended the global Metaphor Users Conference in San Francisco. It was at this conference that I met Bill Inmon. I met a lot of people as there were more than four hundred people at the conference. I met the man who Ralph Kimball had left behind to be responsible for all the data models that Metaphor built.

I was again told, this time by the Metaphor C E O Cathy Selleck, that it was her decision that no I B M Systems Engineers would be trained how to build dimensional models. If my customer wanted one of those they would have to pay for one of her people to come to Sydney to design it. And in the end that is what we did.

In nineteen ninety four and five period the M L C ran a pure research project to figure out how to build dimensional data warehouses. We hired the man Ralph Kimball left in charge to come and help us design the data models. I can assure you that dimensional data models were new to us.

Then it took us nearly eighteen months to figure out how to write the cobol code to populate the data model this man designed. There were two fact tables and twelve dimension tables. And it took us eighteen months to figure out the cobol code to put data into them. It was that hard.

In nineteen ninety five I was the data warehouse architect for the I B M retail banking system being developed in Sydney Australia. In that development work I noticed the design patterns for dimensional models because it was my second dimensional model I had worked on. Knowing how hard it was to write the cobol code for loading a dimensional model I bought a cobol compiler and I wrote template cobol programs to load data into a dimensional model.

I then gave these templates to the programmers on the project to be copied and then updated by hand to reduce the development time.

In nineteen ninety six I was hired to launch the Asia Pacific Data Warehousing practice for Hitachi Data Systems. This was basically a defensive measure to keep H P and Sun out of Hitachi mainframe accounts. One of the men who had worked for me on the I B M project came and worked for me at Hitachi. He was the second best cobol programmer I ever met. Much better than me. I gave him some time to create the ability to write a cobol program that would take one of the col templates, apply changes defined in a file, and then produce the finished cobol program.

I did not write that program. I merely asked this man if he felt it was possible to write. And he wrote it in under 30 hours. That’s how good he was at writing cobol. I didn’t even know if the program was possible and he was able to write it in 30 hours.

Because we had that tool kit we were able to offer fixed price dimensional data warehouses for three hundred thousand Australian dollars in Australia and U S dollars in Asia. This extra money was for travel and accommodation.

So as a global thought leader? I wrote the worlds most productive E T L tool in nineteen ninety five and got it upgraded in nineteen ninety six.

I then migrated that E T L tool to C plus plus in 2002 at the suggestion of Ralph Kimball who had become a good professional friend of mine by then.

To give you an idea of productivity levels of my E T L software. That version that was able to use a data dictionary and template programs to generate the final cobol program to be used? That allowed us to reach a mapping rate of one thousand fields per two hundred and twenty hour work month. We worked long hours.

That rate of one thousand fields per work month mapping remained unchanged from nineteen ninety seven until two thousand and seventeen. For twenty years one thousand fields mapped per work month was the fastest in the world and we saw no reason to try and speed up.

In two thousand and seventeen I invented a new way to get to six thousand to eight thousand fields mapped per work month. You can get that software for free from my web sites.

In twenty twenty three that rate went up again to twelve thousand to fifteen thousand fields mapped from a source system to a target data warehouse in one work month. I have had very long days where I have mapped over one thousand fields in a day. An amount of work I used to get paid twenty five thousand dollars for I can now do in one day.

That is one reason I am so sceptical of the use of A I in E T L development. How is A I going to go any faster than fifteen thousand fields mapped in one work month?

And even if it could go faster? What is the return on investment? It can not be very much because there is not that much cost to remove any more.

Lastly I would like to add the link to one of the ideas I am most proud of inventing. This idea helped Sybase sell a lot of data warehouse data models. It also helped me sell two data warehouse data models for one hundred thousand euros per copy too.

You can read all about this idea on the button below.

In summary?

A global thought leader is a man who can point you to ideas he has invented that have been widely accepted and used.

Whether than be source code control. E T L software. Data Model improvements, or anything else.

The main criteria for measuring whether a man is a global thought leader is that he has invented something that no one ever invented before and that invention was widely adopted.

Some global thought leaders only ever invent one thing.

Some global thought leaders invent multiple things that are then widely used.

The vast majority of men never invent anything that is widely used. That is the normal situation for men.

So.

I would encourage men in the data warehousing area to strive to become a global thought leader in their own right one day.

The path to get there is to learn from already established global thought leaders so that you know as much as is possible about data warehousing. And from there? Have a crack at solving some of the unsolved problems that currently exist in the data warehousing area. There are not many of them any more, but there are some.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

Post script.

If you like my blog posts and would like to help me replace some of the five million dollars it has cost me to save men’s lives and defend the rights of men and boys?

Please buy me a coffee on my buy me a coffee link.

As at the time of writing I have about two hundred and thirty thousand dollars in debt for being willing to risk my life to defend those less able to defend themselves.

Thank you in advance for those of you who buy me a coffee.

It is much appreciated.

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Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

As I have recently announced on my channel.

I will be doing some opinion pieces and response videos.

In this blog post I wanted to talk about an excellent blog post Saurabh Gupta recently released.

Firstly, I highly recommend you read Saurabh’s blog post.

You can read it on the button below.

Saurabh's Blog Post

Now.

I will include quotes for the sections I am directly responding to.

In all honesty, I have been arguing most of these points now for nearly thirty years.

It was nineteen ninety six that I first argued that a data warehouse should contain all enterprise data in a dimensional model that was properly cleaned, made subject oriented, integrated and available for direct query to the business analysts inside the business.

Prior to nineteen ninety six we did not have the ability to put all data into the data warehouse.

The development of the E T L system was simply too time consuming and too expensive to possibly put all the data into the data warehouse.

It should also be noted that in that era there was no incremental extract capability from most large systems.

Many large systems were still on tape or they were tape based systems that have been migrated to disk and still operated like they were on tape.

Because of this E T L processing had to be full image dumps of operational systems and then delta detection was performed.

This was very expensive in processing and time consuming in run times.

Prior to nineteen ninety six the mapping rate of fields from source systems to target systems in dimensional data warehouses was one hundred field per programmer month or even less.

The thing that changed in nineteen ninety six was that I wrote my first E T L software.

I single handedly skyrocketed the E T L mapping rate to around one thousand fields per two hundred and twenty hour work month.

This was an unheard of speed of E T L development.

My E T L software made it possible to put all enterprise data of the day into the data warehouse.

My very first project to do exactly that was the Hong Kong Manu life subsidiary in nineteen ninety seven.

Manu life was the largest insurance company in Canada at the time.

The other thing that we were very aware of at that time was the meta data layer over the top of the dimensional models to make the data models easily understandable by business analysts.

Because I had implemented Ralph Kimballs Data Interpretation System in nineteen ninety one, I was well aware of how a Meta Data Layer can be properly placed over the top of a data model to make it easy enough for business analysts to query.

I also want to make the point at this time that when I say business analyst I mean someone with a degree on the business side of the house and not someone with an I T degree.

I T people, in the vast majority, make terrible business analysts.

A business analyst is a man who knows how his business works in great detail and lives, eats and breaths his business.

It is almost unheard of for a man with an I T degree to become even a mildly competent business analyst.

I am one of the few such men I have ever met.

Sean Kelly was one of the few others.

We are so rare we make hens teeth as common as dust on the ground.

So with that short back ground.

Please allow me to quote and then address specific comments.

Quote.

The Modern Data Report reveals how enterprise data is nowhere near A I-ready. A I cannot reason over data that humans themselves cannot rely on.

End quote.

This is the fundamental finding of the paper. Enterprise Data is not ready to be fed into A I systems.

The report then mentions some main findings. I will repeat the findings.

And then I will reply to the specific findings and comment.

I will prefix all my comments with this comment.

Any company who wants to solve all the issues mentioned below are welcome to download my now free E T L software and data models and use them to solve all the problems mentioned for free.

If you would like to have the tool I recommend you give to business analysts so they can answer their own questions then you can get a copy of the meta five single user software from meta five dot com.

Meta five is the current name for Ralph Kimballs Data Interpretation System. Meta five is a play on words because Ralph Kimballs company used to be called Metaphor. So the next generation of Metaphor is Meta five.

When I say Meta five I mean the current version of Ralph Kimballs Data Interpretation System that now runs on windows and is available in a single user edition as well as the enterprise edition.

Meta five has a basic meta data layer that is perfectly adequate to empower business analysts to ask their own questions of their own dimensional models.

Of course, it is not free but the single user version is very cheap.

I am not going to quote a price because meta five retains the right to vary prices for it’s software.

This is the software that Ralph Kimball invented so you can be sure it is worth the money being asked for.

Quote.

Enterprises have modern data stacks, but their data still can’t be trusted or activated: nearly half can’t fully rely on their data for decisions, and most say it isn’t ready for A I.

End quote.

Correct.

From my limited observations of the marketplace over the last fifteen years it appears that the so called Modern Data Stacks have been an overall negative in the world of using data to improve corporate profit over time.

Much of what I read about modern data stacks is so bad that for many years I thought people were kidding and were not really doing what they were talking about.

What is now called the modern data stack was never going to work. It is like the hype about how Hadoop was going to replace databases. The so called modern data stack is a nonsense and was always going to fail.

The so called modern data stack did not address the fundamental issues of data warehousing which are the data models and the ability to put data into the data models. The so called modern data stack sold the snake oil that some how the T portion of E T L could be ignored.

It can’t.

If you leave the T bit out of the E T L you can not rely on your data. You will have data errors. I have known this since my very first data warehouse project in nineteen ninety one.

There are many problems with enterprise systems and they have been around since day one of enterprise systems.

The three main problems are different keys of similar data in different systems, in valid data, and missing data.

They are three different problems but they occur in every enterprise.

If you want to have data you can give to end users in an enterprise you have to deliver that data in a dimensional model and it has to be properly prepared and cleaned.

That we are in twenty, twenty six and this is still the single most severe problem in enterprises using their data is a testament to the result of our industry refusing to take my advice for more than twenty five years now.

Quote.

The real work of data teams is no longer analysis. It’s search, reconciliation, and validation. Finding and confirming data consumes more time than actually using it.

End quote.

Correct.

Because our industry has not taken my advice of put all your enterprise data into your data warehouse and maintain it properly the so called data teams are endlessly searching around for data to answer questions that arise in the business. Then they do E T L on that specific set of data that has now been asked for. Rarely are they putting it into an enterprise data warehouse. They treat it as a one off. Until the next time someone else asks for it.

If you do your data acquisition on demand then you will spend for ever doing data acquisition and cleaning.

The only way to build an enterprise data warehouse properly is to set out from the beginning to place all enterprise data into the data warehouse. To do this you need a very large and comprehensive base data model to start out with.

If your consultants are selling you the idea that it is best to start with a blank piece of paper for your enterprise data warehouse data model? Then please fire them and save yourself a lot of problems.

As I said above. I have been recommending that enterprises put all their data into their data warehouse since nineteen ninety six. Some have taken my advice. Most have left some data out that they have felt they will never need. Almost all of them have regretted that and added that data later.

If your consultants are saying.

Quote.

Start small and just put the most important and most urgent data into the data warehouse and we will figure the rest out later.

End Quote.

Please fire them and save yourself a lot of problems.

In the few accounts I have visibility in to now they consistently have the problem of adding new data because they did not plan to add all data from day one.

Quote.

Context is fragmented across tools, breaking meaning, lineage, and shared definitions: data exists, but the knowledge required to interpret and act on it does not travel with it.

End Quote.

Correct.

In virtually every account I have ever worked in the E T L tool requires it’s own dictionary and the various front end tools all require their own dictionaries.

Further, the data lineage has been appallingly documented in almost every customer I have ever seen that is not mine.

In my very first project in nineteen ninety one the most asked question was.

Quote.

How was this field calculated.

End quote.

In nineteen ninety three I was doing a pilot at the Saint George Bank in Australia. Because of our pilot it was discovered that the banks liquidity ratio was being incorrectly calculated and the bank was in violation of the existing legislation as to the liquidity ratio that banks must observe.

Of course, the Australian government is not really going to shut down a bank for violating their liquidity ratio requirements. But it was considered so bad that the system was shut down because no data is better than wrong data.

Given that experience I realised just how important it was to be able to know and understand how a field was calculated. And yet here we are today and the most asked question in the accounts I talk to is.

Quote.

How is that field calculated exactly?

End Quote.

Of course, because the front end tools have a separate dictionary to the E T L software there is never an understandable link between the front end tool and the data model and then back through the E T L.

My old friend Ernie Ostick from Ardent has designed a wonderful piece of software called Manta that is now the worlds best software to do exactly what I have described here. If you want the best meta data management tool in the world just contact Manta. The price is eye watering but it’s worth it for big companies.

Quote.

A I adoption is blocked by weak data foundations, not model capability. Without semantic layers, standardised metrics, and trust signals, A I cannot reliably trigger decisions or close feedback loops.

End quote.

Correct.

If your data warehouse can not deliver reliable data, then sending that data into an A I is a case of garbage in garbage out.

Your A I will give you answers. And the answers will even seem reasonable. But they will be wrong.

Example. I once did a telco where we replaced Business Objects reports written based on an Oracle Replica of their billing system. There were eighty five Business Objects reports we were replacing using our data warehouse.

Of those eighty five reports precisely NONE of them were correct when written against the replica of their billing system. They were not even able to get one in eighty five correct.

That is how hard it is to get the right answer out of an enterprise level operational system even if you are an expert in it.

A I can not be made useful when it is fed data that is incorrect. And the worst kind of incorrect data is data where the level of incorrectness is so small that it is not obvious and can only be found by comparing it to a properly built dimensional data warehouse.

Quote.

Practitioners are aligned on the fix. Convergence over complexity: unified access, embedded governance, shared semantics, and self-service are the foundations required to close the data activation gap.

End quote.

I could not have said that better myself. In fact I have been saying this for thirty years!

Whether it be Business Intelligence or Artificial Intelligence.

If you want to use the data in your data warehouse you absolutely need to do the same things in the data preparation.

You need to deliver a data model that is simple enough for a business analyst to read himself. If a business analyst can not read and understand the data model then no A I can read it or understand it either.

If your data warehouse data model is too complex for a skilled business analyst to query it himself? Then your AI will not be able to read it either.

I will get to unified access in a minute.

With embedded governance this is critical. Your E T L system should make sure that all the data in your data warehouse balances. It should make sure that records that are suspect are marked invalid in the staging area and not sent into the data warehouse.

Where you are implementing finance systems like the General Ledger or other ledger systems they must balance to the cent. The E T L system should have processes in place to balance the ledgers. It should be able to detect one single cent missing.

There should be one set of definitions for all fields that are published and common. That set of definitions should then be used to feed into the different front end tools that are demanded to be used by the business users.

In this way when the question how was this field calculated arises in whatever tool the business user is using? The time to answer that question is minimal.

Because all front end tools have their own dictionaries you can not expect them to use the one central dictionary as many people claim to hope to do. But you can have them refer to the one central dictionary and then the extra cost of using those front end tools is easier to understand.

Now I want to comment on unified access and self service.

Ralph Kimball and his colleagues invented self service access to data at Metaphor Computer Systems in the early nineteen eighties. To this day, more than forty years later, I have not seen any tool that compares with Ralph Kimballs Data Interpretation System for it’s ability to empower business analysts to analyse their own data.

Sadly, I T has sold the snake oil that what business analysts need is endless dashboards to analyse their data. This has always been a lie.

The vendors had a financial interest in selling dashboards. They got the license revenue per dashboard.

The I T department had a financial interest in selling dashboards. They got the salaries for creating these mostly useless dashboards.

The people who did not have an interest in the creation of endless dashboards were the shareholders, the customers and the non I T employees of the companies that built these endless dashboards.

For thirty five years I have shouted out that the best way to give self service to business analysts is Ralph Kimballs Data Interpretation System.

But not even Ralph would tell people about his own software because it was owned by I B M by then.

I would like to make my position clear.

The single best way to give self service access to data to business analysts is using Ralph Kimballs Data Interpretation System. You can buy single user versions for what can be considered a pittance compared to the return on the investment of using it.

Next I would like to talk about unified access.

This will be more controversial. But it’s about time someone said it.

There is only one piece of business software on the face of this planet that can be truly called universal.

That software is called Excel.

Whether you love Excel or you hate Excel.

You can not argue that it is the single most widely used piece of software in the business world.

I would make the argument that if you want universal and unified access to data.

Then the way to do that is via Excel as much as possible.

Certainly there are cases where the volumes of data to be reported on exceed the approximately one million row limit in Excel. No one disputes that.

However, there is almost no report that is useful to a business analyst that contains more than one hundred thousand rows of data.

I would even go so far as to say that ninety nine point nine nine percent of all reports and dashboards that are of any earthly use to business analysts have less than one hundred thousand rows of data in the actual report.

Yes, the business analyst may need to look at more data underneath the report in the data warehouse during the exploration process.

But I posit that there is almost no report a business analyst needs to answer questions that require more than one hundred thousand rows of data in the report.

I would propose, posit, argue, that the world of A I and Business Intelligence would be greatly improved if the default tool used was Excel.

I would propose, posit, argue, that other tools were only used after Excel was ruled out because the report needs more than one hundred thousand rows or required functions that Excel can not implement.

For example MicroStrategy, now called Strategy, scales to levels that Excel simply can not scale to. You can roll out a Strategy implementation to more than one hundred thousand users. And it can then give interactive access to the underlying data warehouse.

You can’t do that with Excel.

You can make the argument that you can go some way to that with the At Scale product. But At Scale comes with a very significant price tag that only large enterprises are going to consider.

I am prepared to go on the public record saying that for universal and unified access to data, the tool that is at the top of that list is Excel.

I am prepared to say that unless Excel can not deliver what is needed then it should be very strongly considered.

Because I have made such a controversial statement please allow me to follow it up with this.

With meta five it is now possible to store the S Q L to be used in a report in the cloud. Meta five can read that S Q L from the cloud into the single user desktop. It can then apply parameters to the S Q L and then send the S Q L into an O D B C connection to read the data.

For example.

If you are a retailer and you have twenty region managers who all have a set of daily reports they receive that are in Excel.

It is possible to use Meta five to generate twenty sets of their daily Excel reports that contain just the data for each of the region managers. The data is embedded into the Excel workbooks.

The region managers can then read those reports on disconnected remote devices as they wish. There is no round trip back to any data warehouse to read the report or to click on the Excel filters.

Of course, if the design point is to put the data into the Excel workbook, then there is processing time to do that. This becomes the limiting factor for using Excel with embedded data to produce reports and dashboard.

Everyone is well aware of this limiting factor.

When this processing takes too long then Excel can be made to make the round trip to a central data warehouse to query data.

Quote.

Almost seventy percent of respondents say their data isn’t clean or trustworthy enough for A I.

Sixty five percent say their data lacks the clarity and business context A I needs to be useful.

End quote.

Correct.

This is a repeat of much of what has been said above. If you do not use dimensional models and if you do not have proper E T L you will have a case of garbage in and garbage out for A I usage of your enterprise data.

I would go so far as to argue that in order for data to have clarity and context and to be in a form that can be queried.

Then it is necessary to deliver the data to the business analyst or A I in a dimensional model.

I built my first dimensional model as a prototype in nineteen ninety three. I made some serious mistakes.

I built my first proper dimensional model in nineteen ninety four and five. Once I had it right and it worked properly I knew and understood why a multi level dimensional model was by far the best data model to give to a business analyst.

Michael Saylor at Strategy figured out the same thing at about the same time. He committed Strategy to only being able to read multi level dimensional models. Today Strategy reigns supreme at the top of the Business Intelligence Tools stack because of that decision.

Just as a side note. It is now possible to read Strategy multi level models in Power BI. Please ask me in a D M if you would like that link.

Quote.

Eighty percent of respondents rank a semantic layer with standardized definitions as the most important enabler of A I: above A I tools themselves and above faster processing.

End quote.

Correct.

If you are going to give access to data to a business analyst or an A I?

Then you need some form of semantic layer that standardise definitions of data. It’s hard to believe we are in twenty twenty six and we still have to say this.

Ralph Kimballs Data Interpretation System contains a very simple semantic layer. This semantic layer makes it very simple for business analysts or A I to read and understand what the data underneath the semantic layer means.

This is so simple that it can be used as a starting point for your own development for your own company.

If you want to standardise on the Meta five meta data layer that would be a good start if you have no meta data layer today.

Quote.

Most of the respondents suggest that discovery is where this gap first becomes visible. Eighty nine percent of respondents say finding the right data is among their top three time drains.

End quote.

Correct.

All the way back in the nineties I had a slide for Ralph Kimballs Data Interpretation System.

The slide said that without D I S the business analyst would spend seventy five percent of his time searching for, cleaning, reconciling and gathering data. He would then spend twenty five percent of his time doing actual useful data analysis.

The slide then said that with D I S the business analyst would spend twenty five percent of his time searching for, cleaning, reconciling and gathering data. He would then spend seventy five percent of his time doing actual useful data analysis.

The slide pointed out that D I S would triple the productivity of some of the most valuable people in the company.

Thirty years later we have a survey that finds that eighty nine percent of respondents are saying what we knew in the early nineties. Finding the right data and collecting it is a big time drain. A problem where we knew how to triple productivity more than thirty years ago.

This is an example of why I am so disappointed with the men in my industry sector. We have known how to solve these problems for more than three decades. And yet here we are. We can read a survey where fully eighty nine percent of the respondents say they have a problem that we knew how to solve thirty years ago.

And the reason these respondents have this problem is that my peers in my industry refused to take my advice. The men in my industry chose to listen to the snake oil salesmen at the vendors rather than listen to me.

Oh well. Eh?

Quote.

Ninety three percent of respondents say they encounter conflicting metrics. Nearly half do not fully trust their own data, and sixty eight percent explicitly state that it is not trustworthy enough for A I.

End quote.

Indeed, not only is their data not trustworthy enough for A I. It is not trustworthy enough to be used in general.

Here is a short story. This really happened. I am not making this up.

In Australia in the nineties there was an insurance company called A A M I. All Australians know this company. A friend of mine won their data warehouse project in nineteen ninety four.

I tried to give him advice and help him out to make sure his project was successful. I did this just to help him be successful and to make data warehousing more successful in Australia.

He lived in Melbourne and I lived in Sydney so it was not like I wanted to steal his client.

The project went on for two years and what my friend did was build four separate data marts feeding data from the many different insurance systems.

He had to do this because A A M I had many operational systems for their different business areas.

Of course, the numbers did not add up and the project was deemed a terrible failure.

By this time I had moved to Hitachi Data Systems and A A M I had a mainframe computer from us.

So I went into A A M I and I was trying to help my friend and help A A M I salvage their two years of investment.

But being from an I T vendor I was not allowed to speak to the business managers.

After a full year of going to talk to the D B A Manager at A A M I about their now failed data warehouse project he finally gave me permission to speak to the director of marketing and two of his senior business analysts.

What we were proposing was to build a single integrated data warehouse.

The data warehouse would be integrated, subject oriented, and historical.

From the data warehouse we would then feed the four data marts so that all the numbers added up and they could have confidence in their data.

I did a demo and it was very well accepted by the two business analysts.

The director of marketing left after five minutes. He had zero interest in what he called technical mumbo jumbo.

The demo was from eleven A M to midday.

After the demo the sales representative and I drove back to the Hitachi Office.

Our office was actually in the same street and only about two hundred meters from the A A M I head office.

The Hitachi Branch Manager was standing on the curb and signalled us to come to his office.

When we got into his office he was furious. He said that he had just had the Managing Director of A A M I on the phone demanding that he come to his office at one P M and he was very unhappy with us. So what the hell had we done?

I explained what happened and the branch manager said that I should come with him to the meeting.

We walked into the office of the Managing Director and we were not even offered a seat.

He literally yelled at us for a full five minutes about how I T vendors were to stay the hell away from his business people.

After he finished I asked him if I may ask him a question.

He said yes.

I asked him to please tell me what he would estimate the return on investment has been for the four data marts that had been built. Meaning what new profit had been created that could not possibly have been created without them.

He said zero.

I asked him if he would please be kind enough to tell me why the return on investment was zero.

He said that the numbers from the different data marts do not add up so the management team does not trust the data and does not use the data marts in their management decision making process.

I replied with words to the effect.

Yes. That is true. I know that. I warned my friend you hired to do this job three years ago that this would happen if he did not take my advice.

I have been coming here for over a year trying to save this investment and to help you make more profit.

The way you can save this investment and make more profit is to have a single, integrated, audited, validated, balanced data warehouse that feeds your data marts so you can trust the data.

He looked at me hard and asked how much is that going to cost me.

I told him it would cost three hundred thousand Australian dollars.

He yelled at me.

Quote.

And not a penny more.

End quote.

Then he said to the Branch Manager I want the contracts on my desk by Friday for sign off.

I want your guys to get started as soon as they can and to make this project a priority for your company.

I want this data warehouse thing as fast as you can possibly deliver it.

Now get out of my office and don’t be bothering my business people again!

When we got back into the car the branch manager asked me what the hell happened in there.

I said he saw a professional salesman at work.

I said A A M I has a problem.

They need good information to better manage their business.

They have spent nearly three years and over two million dollars to get the wrong numbers that are worthless.

I offered to save the two million dollar investment and offered to give them the right numbers so they can make more money.

And I offered it for three hundred thousand dollars.

And you saw, the managing director bought that deal.

For anyone reading this post.

I can assure you that the Managing Directors and Chief Executive Officers of companies want the right numbers on their reports in their senior management meetings.

When they are trying to decide what projects to approve and what new budgets to approve?

They rely on the numbers in the business cases presented to them.

If they suspect the numbers in the business case are not one hundred percent accurate they will not approve the business case. This is normal.

To get a business case approved by the senior management team for any significant amount of money for any significant project you have to have the correct numbers.

It only takes presenting incorrect numbers once to destroy your credibility and end your career at that company.

This is how important it is to make sure the data warehouse is integrated, audited, validated and balanced to the operational systems.

It is the same with A I.

Senior business managers are not going to believe the outputs from an A I if they do not believe the inputs.

It’s that simple.

Now that I have repeated that story from nineteen ninety seven it is worth repeating this quote knowing that it is fully twenty nine years later.

Quote.

Ninety three percent of respondents say they encounter conflicting metrics. Nearly half do not fully trust their own data, and sixty eight percent explicitly state that it is not trustworthy enough for A I.

End quote.

It is very sad that after twenty nine years men are still building data warehouses where fully sixty eight percent of the respondents to a survey say that their data is not trust worthy.

Of course, not all sixty eight percent will have a data warehouse.

But I would bet more than eighty percent of the respondents have a data warehouse of some sort or other and that they don’t trust their data.

I have many war stories about data not being trustworthy.

The Barings Bank debacle in nineteen ninety five is what happens when you don’t have a data warehouse doing fraud detection.

Quote.

We asked practitioners what would improve most with faster, more reliable access to high-quality data. The responses show that speed improves first, cited by eighty seven percent , followed closely by confidence at seventy eight percent.

End quote.

Correct.

As I noted above. If business analysts are given self service access to the data warehouse using meta five then their speed of data analysis will vastly speed up. This is so well understood that eighty seven percent of respondents to the survey said they felt they would speed up their data analysis if they just had the right tools, not even knowing what the right tools are.

Of course, faster, more reliable, self service access to data will also increase confidence in the data because it’s easier to find the errors.

To give you a real example. When using Ralph Kimballs Data Interpretation System the time it takes to answer any individual question is around five minutes and often faster than that.

A business analyst can simply walk up to a P C and get the answer to virtually any question in five minutes or less.

What one of my customers did was put a P C in the board room.

At the quarterly board meetings the operator of that P C was to answer any questions asked by any board member during the board meeting.

He was expected to answer any question inside five minutes.

The result was that when business cases were being proposed and a board member asked a question that the proposer of the project did not know the answer to.

Then the question went to the operator of the D I S computer and he was to answer the question inside five minutes.

The net result was that the board was able to approve, or dis-approve, business cases in the one board meeting.

This was opposed to having the person come back with the answers to questions and the business case in three months time.

The net result was that the productivity of the board meetings more than doubled. They could reliably hear more than two times the number of business cases than had been previously possible.

As a result the best business cases floated to the top and were approved. In the past a good business case might be lost simply because the presenter did not have the answers to some questions asked by board members.

The result showed up in the company results. The company I am talking about made vast improvements in their profitability in the period that this business analyst was sitting in board meetings answering the questions that came up.

When he left the company this practice was stopped.

It was no surprise to me that the companies business results went back to what they had been four years earlier.

Quite amazing really.

In Summary.

I would just like to summarise what I have said in reply to Saurabh’s original post as an opinion piece.

Saurabh has conducted a survey that appears quite well run and quite detailed.

We do not have the actual survey questions and the list of respondents.

However, I believe we can trust the findings of this survey because they almost perfectly match my experience.

Indeed, I am of the opinion that the findings of this survey here in twenty twenty six are something of an indictment on the men in our industry.

The men who are my peers.

That our industry segment is having the same problems that we solved thirty years ago is an indictment, not just an accident or anything else.

The first area is data models.

That our industry segment has not widely adopted industry standard data models for data warehouses is an indictment on our industry.

That there are still men in our industry segment who say that a company in a standard industry segment should start with a blank sheet of paper for the data model is an indictment that they are still in our industry.

In the zeros it was arguable that there were still men saying a data warehousing project should start with a blank sheet of paper.

This is because the starting price for an industry standard model was one hundred thousand euros.

Now that I have made a base industry standard model available for free?

It’s an indictment on the men in our segment that they are not using it because they want to make more money developing their own models. Basically they are gouging their customers and giving us all a bad name.

The part eye am going to play in fixing the area of data models is the creation of mega models.

I am working on two mega models with partners.

There are plenty of other large operational systems where the very best men in our industry could build a mega model.

My time is limited and I will only partner with one company per mega model.

So those who wish to get into the mega model business?

They are best advised to pick the mega model they would like to develop and then ask for my help.

You will have to make your business case to me as to why you believe you will be successful in building your mega model for your large operational system.

I will only help those men who are very well qualified to go into the mega model business.

The second area is E T L.

For my sins I am supporting some S S I S packages.

It is insane how long it takes to make changes to such packages.

For those of you who do not know.

I am expert in Data Stage and Informatica.

I have written a great deal about E T L over the years.

The simple facts of the matter are now as follows.

In nineteen ninety six I invented a way to write E T L at the development rate of approximately one thousand fields mapped from source to target in a two hundred and twenty hour work month.

I rewrote my cobol E T L into see plus plus in two thousand and two at the suggestion of Ralph Kimball.

This is the software now known as see T L.

See T L has evolved a great deal over the last twenty four years.

From nineteen ninety six until two thousand and seventeen the fastest way to develop E T L was with my software.

The rate at which E T L could be developed was one thousand fields mapped per two hundred and twenty hour work month.

We used to develop E T L using my software and then at the end of the project migrate it to whatever the client wanted to install.

We have such migration capabilities for both Informatica and Data Stage.

The migration from see T L to either Informatica or Data Stage at the end of a project took two weeks work.

And yet the men in our industry segment have not used see T L and thereby over charged their customers for E T L development.

Today the free version of see T L can be used by a highly skilled data warehouse architect to map between six thousand and eight thousand fields per two hundred and twenty hour work month.

This is more than five times the productivity of the next best tools such as Informatica and Data Stage.

Men in our industry segment are not willing to use the free version of see T L and then migrate it to whatever tool they want to go live with.

Thus over charging their customers.

This is again an indictment of those men in our industry segment.

The paid for versions of see T L are now hitting productivity levels of twelve thousand to fifteen thousand fields per work month.

I have had very long working days where I have mapped more than one thousand fields in a single working day.

My point is that in our industry segment men are still using tools like Informatica and Data Stage and writing E T L from scratch.

Using these tools provides a productivity level of less than one thousand fields mapped per work month.

They are doing this when the leading edge peak productivity is now up to fifteen thousand fields per work month.

Those men are gouging their customers and they do us all the dis-favour of harming all our reputations.

Lastly, I want to comment on development of front ends.

Since I sold the first copy of Ralph Kimballs Data Interpretation System in Australia in nineteen ninety one?

I have said that the most appropriate person to perform data exploration and data analysis is one of the five smartest business analysts in any large organisation.

I have said that I T people have no place performing data analysis because I T people have no clue how businesses work.

The I T industry has done the exact opposite of my recommendations so as to line their own pockets for useless work.

We are now reaping what we have sewn.

I T people are widely considered a joke on the business side of the house.

I was recently talking with the C E O of a company.

She asked me directly.

Quote.

Why are I T people so arrogant when they know so little about business?

End quote.

She genuinely wanted to know how someone who did not know the difference between a debit and a credit could be arrogant about their knowledge of business.

So I explained that to her.

I will say it here again in twenty twenty six.

I T people have no place in performing data analysis.

After more than thirty five years in business intelligence it is my considered opinion that the only people who should be performing data exploration and answering business questions are business analysts.

Primarily it should be men with business degrees who live, eat and breath their business.

I would also argue that no dashboards should be created by I T until the business analyst gives them a working prototype in Excel to show the I T people what to do.

In the last thirty years my experience has been that the vast majority of dashboards I have seen developed, more than ninety percent, have not been used for any significant period of time.

They fall into dis-use very quickly.

My experience has been that in the vast majority of cases the idea of the dashboard has been pushed to the business by the I T shop.

My experience has been that the I T shop has pushed the business into having dashboards to answer lots of business questions.

My experience has been that a single meta five P C would have provided a far better solution.

This is because the business analyst could have answered his own questions without the need to get in the I T queue and would not need to explain his question to anyone in I T.

After all this time I am more convinced than ever that the best way for a large enterprise to sustainably increase profitability over the long term is to give the five smartest business analysts a copy of Meta five and access to as much data as possible.

My opinion is that the data should be in a dimensional data warehouse and that the meta data layer provided can just be the simple Meta five dictionary. If there is more meta data available it can be added to the see T L dictionary manually.

My opinion is that in order to detect out of the ordinary situations meta five jobs can simply be scheduled to go looking for those unusual situations and can report on them using Excel and emails.

If you wanted to use A I to do the same scanning and reporting?

Then that would be fine too.

However it is cheaper and easier to do in Meta five.

This is where I think we are at.

And if my industry segment took my advice in this post?

Perhaps in five years time when Saurabh performs a similar survey some of the numbers will be far lower than they are today.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

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Hello and welcome to this update.

I really appreciate you being a subscriber to my Substack.

Thank you.

In this update I just wanted to let you know that I will be producing more opinion pieces as “response pieces” to articles released by other thought leaders in the area of Business Intelligence and Data Warehousing.

The reason for this is simple.

Response videos and opinion pieces that are responses to articles generate more interaction with readers.

All social media sites reward more interactions.

I have already released everything a man needs to start his own data warehousing business for free.

There are “paid for” versions of my SeETL software and my data model verticals, but the base levels are free and source code. There is no taking them back.

They are all any man needs to start their own data warehousing consulting company.

You can get the latest version of all my freebies on this link.

Pete's Freebies

If you would like to be on my actual email list for Instant Business Intelligence you can get on that email list on this button.

Join Pete's Email List

I do not send out many emails since there are so few people on my email list.

I have over 6,000 people on my email list that I have accumulated over the years.

I offered them the opportunity to subscribe to my new email list because most of those people are no longer in Data Warehousing.

Very few of them came across to the new email list which indicates the lack of interest in making more profit in corporations now days.

On the header of my Substack you can see a menu item for “Opinion” and this is where all the new Opinion Pieces will be.

In Substack you can control the emails you get from a publisher.

So if you do not want to receive my Opinion Pieces as emails you can go into the Newsletter menu item and you can turn off Opinion as one of the newsletters you get.

I will continue to release posts for other sections but they will be relatively few and far between.

Having published so much over the last 15 years there is little point repeating what is said in those posts.

I may release updated versions of some of those posts over time.

In other news I now have a paid subscriber! Hooray!

As promised the “benefit” of being a subscriber is that I promise to answer any questions from a subscriber.

If the subscriber wants the answer privately that’s fine.

If the subscriber is happy for me to answer the question publicly that’s fine too.

Subscriptions are currently USD5 per month or USD40 per year.

You can subscribe on this button.

Subscribe now

That is all for now.

Thank you again for being a subscriber on my Substack.

I really appreciate you for being here.

I would like to get back to being one of the most widely read people in the Business Intelligence area as I was in the late 1990s.

Our industry segment is now a laughing stock on the business side of the house.

If men are to re-establish their professional reputation and respect in the Business Intelligence and Data Warehousing area?

Then they are going to have to finally listen to me and take my advice.

Men have not been willing to listen to me in any numbers since 2002 or so.

The state of our profession reflects the fact men in our industry segment did not take my advice.

If you want to be respected in your profession of Business Intelligence and / or Data Warehousing?

You would be well advised to take my advice.

Up to you.

Lastly, I will do some opinion pieces on Artificial Intelligence.

I am not at all bullish on AI over and above BI.

There is much more profit to be made by companies by using Business Intelligence than there is in using Artificial Intelligence.

As we stand today?

There is still no technology investment a company can make with a higher return on investment than doing Business Intelligence properly.

This has been true for thirty years and I do not see it not being true in the next thirty years either.

That Business Intelligence and Data Warehousing has been done so poorly is a reflection on the professionalism of the men in our industry, not the principles of our industry.

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I wish you a good weekend.

Best Regards

Peter Andrew Nolan.

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Since I am banned off Medium? Anyone who wants to put this in his comments is welcome.

You can go to his post on the button below.

Joes Post

Tech employes started their path on becoming disposable some time before I started my very first trainee programmer job on 1982-01-18. In Australia we start our university year in February.

The deal we had was that we were to work for 32 paid hours per week at our jobs and we had 8 hours per week to attend university classes in 9-6 time that were not available after 6pm. When University was not in session, which was 20 weeks a year, we were to work 40 hours a week at our job.

Of course, we were paid pittance since we were not useful. Though, to be fair, on my first day I learned the coffee desires of my team and I was the coffee maker. I was very happy to be so. I then learned how to make cardboard folders for program listings and set about the task of printing program listings and filing them in the library cabinets properly.

A week or so after we started university I walked past the desk of one of my women peers and saw that she was doing her university assignment we had for Math101 that week. I was on my way to do my very important coffee making job for my team.

So I walked over to her desk and asked her if she was doing the Math101 assignment. She asked me if I was stupid because it was obvious that is what she was doing.

I told her I was curious as to why she was doing it at her desk in work time and could she please explain that to me. She asked me if I was a nazi and had some how become the “work nazi”. All very hostile answers for innocent questions. If she was not doing something she considered was wrong there would be no need for such comments.

So she said that yes, she was doing the Math101 homework we had been given and “what business is that of yours?” I replied that she worked for the same company I did and that she signed the same contract as I did and that she was violating her contract, so it was my business.

I asked her if her boss knew she was doing this university work and she said yes.

I asked her if she had any problems with me talking with him about it. She said no.

There was more said but let’s keep this short.

So I went to her bosses desk. His name was Richard and we all called him Dick.

I asked him if he knew his employee, aptly named Karen, was doing university work while on work time. He said sure he knew that and wondered why I was asking him about it. I said that this is considered stealing because she is paid for 32 hours a week to do as he asks her, not to do her university work.

He laughed and said “You are not married are you.”. And I said no, I was just 18 years old and currently not in any relationship so no plans to get married any time soon.

So he explained in words to the following effect. These are not his exact words. I have shortened the conversation a bit.

“When you get married you will find out that a man can not even get his own wife to do what he wants her to do. So it is simply impossible to get a woman employee to do what you want her to do. You can ask. And she can just say no. There is nothing to be done when a woman says no, she will not do as you ask.

The situation is that the government has issued quotas for women. We call them “affirmative action quota women”. We must meet those quotas or we will be heavily fined by the government. So we hire “affirmative action quota women” to avoid the fines. We can’t get them to do anything. But if we fire them we just have to hire another woman and we have to go through the whole charade again. So it’s cheaper to just keep the ones we hire and let them sit there and do nothing.

Please just think of a woman in the office as another form of taxation because that’s pretty much what they are, another form of taxation we all just have to pay.”

I asked what would happen if I did my university work while in the office. He said I would be immediately fired because I am a man and I am expected to do as I am asked by my manager.

Yes. That was February 1982. After I was told this I noticed that of all the women who worked in our office only one of them was actually doing what she was asked to do. Her name was Caroline. So I asked Caroline why she was not talking to her peers about doing what they were asked to do. She said that getting other women to do their job was none of her business. I pointed out that she would be tarred with the same brush across her career. He reply was “well that would be unfair to me”. I pointed out that while she tolerates this she will be tarred with the same brush, fair or not.

When I interviewed at IBM in September and October 1985 I specifically asked the managers I was interviewing with if IBM was subject to the same legislation and did IBM participate in hiring “affirmative action quota women”. When I was asked why I was asking I explained my current employer is subject to that legislation which means I am paying a “woman tax” out of my possible earnings and I didn’t like that idea.

I was assured by all managers interviewing me that IBM was not subject to this legislation and that IBM followed two founding principles.

1. Respect for the Individual

2. Pay for performance.

So I joined IBM in January 1986.

By October 1987 I already had my deep suspicions that IBM was doing “affirmative action quota women” and simply not saying so. Indeed, denying so. I was dragged into IBM HR for the first time in October 1987 for doing my job.

A part of my job was to review source code at walkthroughs. I was particularly gifted at this because I had what is commonly called a “photographic memory”.

The “walkthrough” is the number one error detection mechanism in large systems development. We “walkthrough” everything. The standard practice at IBM was that before you asked anyone to perform a “walkthrough” of your deliverable it must be completedto the very best standard you can achieve. Records were kept and statistics were maintained. Those with the most bugs reported would be moved to different projects or encouraged to leave. Those with the least bugs and best deliverables, could look forward to pay rises and promotions.

So “code walkthroughs” applied to source code. And I was VERY good at these. I was also very good at test case results walk throughs and finding bugs in code that looked like it was working.

I had worked on a system called COBRA 1.0. I completed the Hong Kong / China install in September 1987. I was then ill for three weeks and came back to work in October 1987. The Cobra 2.0 release was due for completion on December 31st 1987. I was asked to please help out with testing and code walkthroughs to improve the quality of what was being delivered.

Well? The code I was given to walk through by the women was very low quality. I did my job professionally. I documented all the errors and explained how to fix them. The women would run crying to the bathroom and us men were very frustrated that they were so fragile that when we tried to help them make their code better they ran crying to the bathroom.

I was hauled into IBM HR and told to “go easy on the women”. I said no. I said I was a not a sexist and that I would treat women just exactly like I treated men, as women had said for many years they wanted to be treated. So I was no longer offered any walkthroughs for women. I was only offered walkthroughs for men.

The result of this was that COBRA 2.0 was a disaster of biblical proportions. I had only scratched the surface. All the additions of 2.0 over 1.0 were rubbish and didn’t work. I was sent to Malaysia to implement Cobra 2.0 in May 1988 and I could not even get it off the tapes. I won’t go into details here, but it was a disaster of biblical proportions.

The project was almost cancelled after lunch on day 1. It was only my promise to “fix it” that kept the project running. Also, I told the CFO of IBM Malaysia I had been lied to about the state of the system by my now IBM Manager. He was SHOCKED to hear me say that I gave my word I had been lied to and told that the system was properly tested and functioning in the Philippines.

At the end of 1988 I was awarded a HUGE promotion to be the System Architect of a system named PRISM 4.0 which was the internal pricing system in IBM Asia Pacific. The youngest ever man to hold such a senior position.

In December 1989 there was a very serious issue with the implementation of COBRA I did for the IBM Australia Export business.

If you want to listen to a very amusing video about it you can watch the video below.

To summarise the video.

The COBRA Billing system had been down for 2 weeks. Because it was printing the Air Way Bills as well as the invoices no PCs had been shipped out of the country for 2 weeks. You cannot clear customs without the Air Way Bill. The issue had been raised at the weekly Monday morning meeting with the head of IBM Asia Pacific that all the country Managing Directors attended.

The Managing Directors were concerned they would miss their quotas because of this problem. The Managing Director of IBM Australia was told that if anyone missed their quota because of this problem he would be fired. And that problem ended up on my desk at about five minutes past Midday that Monday.

A woman named Helen had been running around like a chicken with her head cut off for two weeks and it turned out that this problem is what she was failing to fix. I fixed it inside 8 hours.

I then had two weeks of invoices to print off on twenty pages per minute laser printers. So we were printing invoices all over IBM Offices in Sydney until 3am. We did not have many of these new and very expensive twenty pages per minute laser printers.

In short. I saved the Managing Directors job by working a solid 36 hour day.

On the Thursday we had the annual Christmas Meeting and Helen was given a $A1,500 award for “trying really hard for two weeks to solve this problem”. After I saw that award I cornered the manager who had interviewed me in 1985 and was now my good friend. I respected him very much and he respected me.

We talked very quietly in a corner of the presentation area and I said to him “You told me four years ago that IBM did not have an affirmative action quota women program. You have told me many times since that IBM does not have an affirmative action quota program. But Helen just got a $1,500 award for “trying really hard to solve a problem” when we all know she is as dumb as a box of rocks. So I think we DO have an affirmative action quota women program. What do you say?”

And I will never forget his reply. It was:

“I have been assured that if I ever say that we have an affirmative action quota women program I will be fired. So I am absolutely telling you that we do not have an affirmative action quota women program and if anyone ever asks me if I told you we do I will most strenuously deny I ever said that. If you think we have an affirmative action quota women program you absolutely never heard that from me.”

Which, of course, was his way of saying: “Yes, we have an affirmative action quota women program but I can’t say that so I am going to say something that gives me absolute deniability.”

I thought about it for 30 seconds and decided I would leave software development and told him so. He asked why. I said:

“To create very high quality software that is extremely reliable takes very skilled and reasonably expensive people. To create buggy software that crashes all the time can be done by cheap people anywhere. There is no future in software development here. I will leave my job before my job leaves me.”

By 1996 most of the jobs in the International Software development were relocated to Malaysia because bad software can be developed by cheap people anywhere.

And THAT, my dear readers, was the beginning of making tech employees disposable. When you let women in and allow women to create buggy software because they will cry and run to the bathroom if you try and help them improve their software? You are at the beginning of a slippery slope.

Firstly software development was moved to places like India. And later? Indians were moved to places like Microsoft in the US at cheap rates on H1B visas to develop buggy software that crashes all the time.

So, if the product you want is buggy software that crashes all the time? It’s only a matter of time where the cheap people who write buggy software that crashes all the time are replaced by even cheaper AIs that write buggy software that crashes all the time.

Now, if the product you wanted was high quality software that is extremely stable and reliable? Well that takes a very skilled person like me to develop.

That is exactly what my SeETL software is. At least the run time components are very high quality software that are extremely reliable. The SeETL Design Time Visual Basic code is rubbish because I didn’t know how to write C++ to read XML documents in 2004 and so I wrote it in Visual Basic and it stuck. LOL!

This is why tech people are being replaced by AIs. It is because if the product you want is bad software that crashes a lot and is unreliable? AIs can now write software like that cheaper than even the cheapest Indian programmers.

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Best Regards

Peter Andrew Nolan

Hello and Welcome.

Thank you very much for being a subscriber to my Substack.

You may not know that I am the most censored man in the world.

The reason I am the most censored man in the world is that I have been the world’s highest profile man defending the rights of men and boys since I went public on that matter in June 2008.

I have been banned from pretty much everywhere except Substack and Rumble.

Earlier this year I loaded up my back catalog of 1,500+ videos to Rumble and subscribed with the monthly fee.

For my subscription fee Rumble has allowed my videos to stand, not that anyone is watching them.

So…all my political content is on Rumble.

If you want to watch my videos that are related to the mass murder of men by proxy in the divorce courts?

If you would like to watch my videos about running your own business and making money in your own business?

You can go to my suite of rumble channels on the button below.

It’s all free content.

Pete's Rumble Channels

Here on Substack I will continue to post about Business Intelligence and Data Warehousing.

I have discovered that I can repost old posts and they go out as emails.

So that is a good way to cycle through the older, very valuable, posts so that new subscribers see them.

If people also adopt my BI4ALL data models?

That would be great too.

But the main reason I am on Substack is to give away free copies of my SeETL software and have it widely adopted.

I used to sell SeETL for EUR20K per copy.

I sold three copies to the richest man in Australia for that amount each.

I actually sold an “all you can eat” copy for EUR30K to Key Work Consulting in Germany in 2007.

Key Work Consulting

My SeETL Software vastly reduces the costs of ETL development and support.

And by “vastly” I mean by 50%+.

There are “paid for” versions of my software also available.

The newer version has features that allow ETL developers to map up to 1,000 fields per day in a 15 hour day.

At least, I have done that myself.

In a normal 8 hour working day it is now possible to map 500-600 fields from what I call a “Large Operational System” (LOS) to the data warehouse.

I have literally invented the future of data warehousing and how data warehouses will be built in the future.

I am working on “getting the word out”.

My censorship because of my whistleblowing on the criminal nature of the divorce courts makes it hard to get the word out.

So if you have other social media or email lists that you can use to tell people that SeETL is now free and open source?

Please feel free to pass along the message.

Best Regards

Peter Andrew Nolan.

PS. You can get all my freebies from my Instant BI web site.

Instant BI Web Site

I wish you a good day.

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

As I have recently announced on my channel.

I will be doing some opinion pieces and response videos.

This is clearly an opinion piece.

A lot of people have asked me this question.

Peter, why don’t you create classes for ETL development and data modelling?

That’s a fair question and so I thought I would answer it in an opinion piece post.

The simple answer is that individual men who want to learn how to do data modelling and ETL development are not my prospects to do business with.

Look how many people bought Ralph Kimballs books.

Look how many people took Ralph Kimballs courses.

Very few of them ever became good data warehouse architects.

Ralph asked me to review his first book and I did.

I launched Ralphs first book in Australia.

I attended his very first class in Australia and had 8 other men from my company come along as well.

So I know a lot of men who bought Ralphs books and did Ralphs classes.

Less than one percent of them went on to actually be good data warehouse data modelers.

So what’s the point of training people to do this?

It’s a complete waste of time more than ninety nine percent of the time.

I am now giving away models that are superior to anything Ralph ever talked about and men don’t even want to learn from those models for free.

Today, individual men want to get everything for free and expect to some how figure out how to make money.

Their problem is that in creating a culture where men also expect things for free as women always have?

They have done themselves out of a job.

If a man really wanted to be my student and wanted to learn from me?

He would offer me some money for my time and then I would teach him.

But men will not even buy me a coffee for all I have released for free.

This is why I don’t run any sort of educational course or classes publicly.

The men who might sign up generally want everything for free or very cheap and in doing so they have no idea how to run a business.

So.

Moving on.

Who are my prospective business partners?

Because I have been so widely slandered I can not make sales directly to companies any more.

My prospective business partners are men who run their own data warehousing company and would like to make more money doing what it is they are already doing.

I have helped many individual consultants along the way.

If you are an individual data warehousing consultant running your own company?

You are welcome to use my freebies to help you make more money.

Any individual consultant who bothers to learn how to use my data models will make much more money in his business.

If he learns how to use See TL he will win a lot more ETL development work.

And good luck to such men.

If they want to ask me questions they can pay me for my time.

None ever do so they are not prospective customers.

My prospective customers and business partners are the owners of BI companies.

These men don’t need classes on how to design data models.

These men don’t need classes on how to build ETL.

These men don’t need classes on how to run a business.

These men want a way to make more profit for their company because they are the owner of it.

So these men want my data models and my See TL software.

And because I am slandered they want them in their own branding.

And because they are business men they know they have to pay me to create a copy in their brand.

They know they have to pay me for each license they sell or use.

Given the training for the data models and See TL is free?

The only money they know they have to pay is for actually using the models and software in production.

And because they make much more money than I am asking for?

They are happy to pay me.

For example?

Way back in two thousand and seven Tobin Wotring of Key Work Consulting in Germany paid me thirty thousand euros for an all you can eat source code license of See TL.

This meant I created a version for his company using his name and logos.

He paid me thirty thousand euros plus maintenance for more than 10 years.

The deal was he could run as many customers as he wanted in his data centre and I would not sell another license to any company based in Germany.

With the help of my software and my training he went on to become a millionaire many times over and his company is doing very well even today.

I also helped Altis Consulting in Australia get going in two thousand and two thousand and one.

I helped Knowledge Net in Saudi Arabia get going.

And of course Sean Kelly and I relaunched Sean Kelly and Associates after Seans time at Sybase.

The men who run these companies do not need classes.

When first meeting me they need deep dive proof that the data models and See TL can deliver them more profit than they are able to deliver today.

This is why my articles are long.

This is why they are deep.

And this is their purpose.

That when men who run data warehousing companies see them they know I am one of the worlds thought leaders in this area.

They would like to figure out how what I offer can be integrated into their offerings to help them make more profit.

So if you are a man who runs his own data warehousing company and you want to sustainably increase your profit?

Go through my freebies in detail.

Get your best people to play around with the prototypes.

Even use my models and software in production at your clients if you want to.

And when you are ready to buy a custom developed version with your product name and your company logo on all the documentation etcetera?

Then you can call me and ask how my schedule is going.

The price will be ten thousand euros for the copy and your first two customers are included in that price.

Then it will be five thousand euros per installed site.

So once you have three sites you have paid me fifteen thousand euros.

If you want to do a deal like Tobin Wotring did all those years ago?

I will do you a deal of ten sites for thirty thousand euros for your custom version of See TL.

That means you are only paying three thousand euros per site rather than five thousand euros per site.

That leaves plenty of money for you in margin if you want to charge what others are charging now which is ten thousand euros or dollars per site.

In fact many of my partners are just using my software and not putting it as a line item on their invoices to their clients.

It takes no time at all to regain five thousand euros from consulting on a data warehousing implementation.

So most of my clients just use my software in production and don’t try and sell it to the end customer.

If you are a man who works for a company that does data warehousing and business intelligence?

You can tell your company owner about our software.

Those people who use my data models and See TL software will be able to grow their companies and make more profit because your costs will be lower than your competitors.

I think that is enough for this opinion piece.

If you have any questions you can contact me on the contact form.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

The post IBI-068-Why-I-Dont-Offer-Classes appeared first on Instant BI.

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

As I have recently announced on my channel.

I will be doing some opinion pieces and response videos.

I recently did a blog post on the question of Data Engineering.

Today I am doing a blog post on Software Engineering.

This post will closely parallel the prior Data Engineering post.

Back in the late seventies and early eighties there were questions about what might be the future for software development.

Software development was so complicated and so difficult and software was so full of bugs in those days.

There was a real question over how could software development be improved.

One of the professions that software development was compared to was the profession of constructing large buildings.

O S three sixty cost around five billion dollars to develop in the sixties.

In large companies software development projects were commonly in the region of one hundred work years with a three year elapsed time for a project.

The ideal project team size was around thirty people with a development period of around three years.

Obviously this was a similar size to a project to build a relatively modest building.

There were larger software development projects such as SABRE.

SABRE was the Semi-Automated Business Research Environment.

It was developed in the 1960s and 1970s by IBM in collaboration with American Airlines.

It became the first computerized airline reservation system.

SABRE revolutionized the travel industry by automating the process of booking flights, managing seat inventory, and handling passenger data.

Over time, it evolved into a global distribution system used by travel agencies and airlines worldwide.

SABRE was of the size of building a very large array of skyscrapers.

So there were modest one hundred year development projects.

And there were projects that employed hundreds and hundreds of developers.

Inside IBM there was a system called the World Trade Advanced Administration System.

I am not sure if World Trade Advanced Administration System is comparable in size to the Semi-Automated Business Research Environment.

In any case.

In the late seventies and early eighties these sorts of systems were under development.

And the question on everyone’s mind was.

How can we increase the quality of the software while also reducing the cost of development?

Learning from the construction industry was one obvious avenue.

We still have buildings standing that were built five thousand years ago.

So it seemed only natural that we look into construction techniques to see what we could apply to building large software systems.

The seminal book of the period was Barry Boehm's book called Software Engineering Economics which was published in 1981.

This book introduced key concepts such as the Constructive Cost Model, which became foundational in software cost estimation and project management.

Boehm closely compared software development with building construction and this is why he proposed the idea of using an “engineering” approach to software development.

I joined IBM Australia’s international software development laboratory in nineteen eighty six.

I was required to read this book as part of my training.

However, as time went on it became clear that the software development profession would not adopt professional standards like the building construction profession.

As part of this I left software development in nineteen eighty nine.

In nineteen eighty nine I predicted that software quality would decline.

I predicted that IBM would outsource their software development to cheap labour countries like India.

Of course, I was right.

Since nineteen eighty nine overall software quality has consistently declined.

Many people have offered many excuses for this.

No one will talk about the real reason.

At that time, nineteen eighty nine, software developers were simply called software developers.

There were no software engineers in nineteen eighty nine because we knew how poor the quality of our software was.

We were very clear that if we were to use the term “engineer” it would be an insult to actual engineers.

However, over time, people who worked in the area of software development wanted to cover over the poor quality of their products rather than to improve the actual product.

So some vendor or other decided to start calling software developers software engineers.

I don’t know who started this nonsense.

But a lot of companies promote this nonsense now.

The implication of calling software developers software engineers was that the quality of the product was similar to the quality of a building built by engineers.

The comment I always use is this.

In Roman times the bridge builders agreed that before the bridge they built was put into service they must prove it will carry the weight the bridge builder claimed it would carry.

And so carts would be loaded up with stones and donkeys would pull the heavy stone laden carts across the bridge to prove the bridge would stand up to the maximum load.

The key point being that the bridge builder had to stand under the bridge while the donkeys pulled the stone laden carts across the bridge.

Obviously, there were no charlatan bridge builders in Roman times.

Any man who wanted to try and be a charlatan bridge builder would be discouraged by this test.

How about self described software engineers today?

Would they risk their life on the quality of their work?

No. They would not.

Would they even risk a weeks pay?

Probably not.

People who call themselves software engineers do not want to suffer any financial loss if they do their job badly.

Meanwhile?

Your average electrician might be killed by accident if he does his job badly.

One of my good friends from school became an electrician and was electrocuted to death when he was twenty four.

Very sadly he left a little baby girl behind.

His wife was very, very lucky in that another good friend of mine decided to marry her and raise the little girl as his own.

Men who are electricians may pay for a mistake with their life.

The same is true in many professions men work in.

I worked in a steelworks and at least one man died each year on the job.

In the two weeks my then girlfriend and future wife, Jennifer, came to do work experience in the library three men were killed.

She could not believe that men were killed on the job.

One day I got permission from the relevant supervisors and I took Jennifer to the plant that I worked on the computer systems for.

This was a relatively clean and safe area of the steelworks.

Not like the blast furnace area, the coke ovens, or the basic oxygen steel making areas.

Jennifer was shocked at the working conditions of the men just in the mill I worked for.

The biggest risk your average software developer runs each day is giving himself a paper cut.

Or maybe he might manage to spill his hot coffee onto his lap or hand.

He does not have to worry about being killed in an accident while on the job.

He does not have to worry about being liable for errors he has coded into his software.

If you compare the penalties for buildings falling down and killing people, or for electrocution of people in a building, to the complete lack of penalties for bad software?

Then you can plainly see that self described software engineers do not design and build their systems to the same quality as real engineers build buildings.

A lot of people are talking about AI generated code now.

My answer to that trend today is the same as my answer to what I saw in nineteen eighty nine.

In nineteen eighty nine I said that if IBM is prepared to accept low quality software then they will move software development to cheap countries like India.

The advent of AI is the same.

If low quality software is acceptable then today an AI can write a good portion of that software if it is well specified enough.

AI can not write high quality software because there is no repository of high quality software from which to learn.

The bottom line is this.

Engineers, doctors, lawyers, plumbers, electricians and many other professions hold the practitioner accountable for the quality of their work.

They all have governing bodies where those who feel they have not been served well can take their case and at least get a fair hearing.

Sometimes they are even awarded damages.

In virtually every profession you need a license to practice.

I mean think about this.

In nearly every country in the world you need a license to even drive a car.

But in so called Software Engineering?

There is no test to pass.

There is no license to qualify for.

There are no governing bodies.

There are no tribunals to hear cases of misconduct or malpractice.

There are no insurance policies you can buy to protect yourself against injury harm and loss from bad software.

There are no standards.

So called software engineering is a free for all where a three month “boot camp” certificate is all that people need to start calling themselves software engineers.

Would you go to a doctor who was calling himself a doctor after a three month doctor boot camp?

No. You would not.

As I mentioned on my previous post I was an IBM Systems Engineer.

I had to go through very tough classes proving my knowledge of IBM hardware and software.

Failure meant that the candidate had to try again the next year.

Two failures meant you resigned your job at IBM.

After my classes I was then qualified to call myself an associate IBM Systems Engineer.

I had to work at that associate level for a year before I was raised to the full level of Systems Engineer.

I was able to be promoted very quickly because I already had four years of experience inside IBM and my subject area in marketing was to advise our customers software development managers.

And as an IBM Systems Engineer I knew my job was on the line with every decision I took.

I knew if I messed up I might be fired.

I spent two years at the standard level of Systems Engineer before I was promoted to Advisory Systems Engineer at the end of nineteen ninety three.

And I can tell you that in nineteen ninety two and nineteen ninety three I worked very hard.

I worked very long hours to distinguish myself from my peers to get my advisory promotion so quickly.

So I know what engineers do.

I worked with a lot of them at the steel works.

I know what IBM developers and developers in other companies do.

I was an IBM software developer.

I advised very large companies on how to improve their software development practices.

I was an IBM Systems Engineer.

And software developers today, and in the past, were not engineers.

The quality of their work and their commitment to maintain the professionalism of the emerging profession has been a running joke for decades.

I sincerely doubt that there will ever be any sincere adoption of professional practices and processes in the area of software development in my lifetime.

Those people who worked very hard to become very good at software development are doing themselves a great dis-service to allow unqualified people to use the same titles.

Back in the days of IBM we had the levels as follows.

Trainee Systems Engineer.

Associate Systems Engineer.

Systems Engineer being the standard full level.

Advisory Systems Engineer.

Senior Systems Engineer.

To get to senior systems engineer you had to do something pretty special.

Men who had been at IBM for thirty years were still on the Advisory Systems Engineer level.

The general time it took a man to get from entry level to Advisory level was five to ten years.

And Advisory level was the level you stopped at unless you did something quite remarkable.

So our IBM customers, when someone was introduced to them at their level, could observe the mans age, and gain a pretty good understanding of how good he was at his job.

Now that people are given grandiose titles with no real testing and proof along the way?

Customers have no way of knowing how good the man is at his job.

This would seem to be the way that software development is going.

The software development profession never even made it to the level of professionalism and respect earned by electricians and plumbers.

If the software development profession wanted to improve the level of professionalism and respect for their profession?

They could always hire me to do that.

I won’t hold my breath for their call.

That is my opinion.

If you have a different opinion?

You know what the comments section is for as well as I do.

Please feel free to share your opinions in the comments section.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

As I have recently announced on my channel.

I will be doing some opinion pieces and response videos.

In the world of social media it is very well understood that response videos and opinion pieces are far more widely viewed than straight up factual videos that are educational.

Personally, I think this is sad, but it is what it is.

This blog post is my opinion piece on the now widespread use of the term data engineer.

The men in my industry segment made it clear they did not wish to hear what I have to say in the early part of this century.

The men in my industry segment decided they would rather listen to the vendors than listen to me.

And now we are twenty years later.

The men in my industry segment are a laughing stock to the business side of the house.

There is no other way to characterize the data warehousing and business intelligence space today other than a laughing stock.

And gentlemen?

It is not our industry that is the laughing stock.

It is the men in our industry who are the laughing stock of the men on the business side of the house.

It staggers me that men are so willing to be a laughing stock.

But men most certainly are willing to be a laughing stock in their profession.

I was recently in a meeting with the chief executive officer of a small company.

She actually asked me why my young peers are so ignorant and so arrogant.

I explained to her that they sincerely believe they are more important to the business than the real business people.

I explained to her that they forget they are the servants of the business.

She asked me about the history of this given how old I am.

I explained that it is a phenomenon across the western world that has been ongoing since the nineties.

I told her that I had objected and tried to teach technology people to be more humble but my colleagues and I were not listened to.

She thanked me for my honest response.

Today I wish to forward an unpopular opinion in this public post.

The term data engineer is laughable.

This is like calling Katy Perry an astronaut because of her 4 minute trip into lower space.

Please allow me to share with you a little bit of history of engineering and engineers.

In Roman times most people could not read or write or do anything more than basic mathematics.

So if a village wanted a bridge built for whatever reason they had to hire and pay a bridge builder.

The bridge had to be built and paid for before the first horse and cart crossed it.

So how did villagers decide which bridge builder to buy the service of having a bridge built from?

And how were they to know they were not being ripped off by a charlatan?

The villagers came up with a test.

That test was that when the bridge was finished, and before final payment was made, they would put rocks in carts and have those carts pulled across the bridge by oxen.

They would load up the bridge with the maximum load the bridge builder said the bridge could hold.

The trick was that that the bridge builder was required to stand under the bridge while this stress test of the bridge was performed.

Of course, if the bridge failed the bridge builder would die.

This was a good way of making sure that charlatan bridge builders would not volunteer to build the bridge.

When you had to guarantee the quality of your work with your life you make sure you know what you are doing.

It’s not a complicated idea.

As much as it will upset people in the data warehousing area?

Please allow me to put this question.

How many self described data engineers would stand under the figurative bridge of their data products where the price of a failure in their data product was paid for with their life?

Of course, we all know the answer to that question is none.

There is no person in the data space, including me, who would guarantee their data products with their life.

Gentlemen.

One of my uncles was a builder.

My very first job outside my home was to stand with my cousin at his fathers building sites and fetch the tools from the men’s trucks when they called for us to fetch the tool.

In this way the builders did not have to climb down from where they were working to fetch a tool that had become necessary to use.

In this way I knew the names and uses of all the tools the builders used by the time I was eight years old.

And yes, one day I was sent on my push bike to the local hardware store to buy a long weight.

Every little boy I knew who helped out the men on building sites were sent on their push bike to buy a long weight.

It was a right of passage for us boys to be sent to buy a long weight.

So right from the time I was a small boy I understood the difference between engineering and building.

I knew that if my uncle and his fellow builders did not build the houses properly someone might be killed when it collapsed.

This is very much more so the case when the building is a skyscraper, when the building is a major bridge, when the building is a long tunnel.

Consider the jet airplane, for example a Boeing seven four seven.

They travel along at one thousand kilometres per hour at forty thousand feet over very wide oceans with no landing strip in the case of needing a reboot.

Skyscrapers, major bridges, long tunnels and seven four seven airplanes all have one thing in common.

They are designed by engineers.

The cost of a design flaw can be hundreds, or even thousands, of lives.

Engineers do their work to a level of quality that they would quite happily stand under the bridge, or bet their life on their product, because they know it’s not going to fail.

Self described data engineers will not stand by their product because they know their products fail regularly.

Self described data engineers are trying to appropriate the respect and the credibility of real engineers, earned over thousands of years, without putting in the work to earn the right to use the title.

This is the same as men who claim to have been in the armed services and served in combat zones when they have done no such thing.

Stolen valour and stolen credibility and stolen respectability are all similar things.

They are all bad in my opinion.

One of the many reasons that these are bad things is that they demean and devalue those men who actually did earn those titles by their actions.

Please allow me to give you an example from my own career.

I was an “IBM Systems Engineer” in the nineteen ninety one to nineteen ninety four period.

To earn the title “Systems Engineer” this is what I had to do.

Firstly, I was already the youngest System Architect ever in IBM Australia.

I was running the technical side of a four million US dollar four hundred work month development project in nineteen eighty nine at the age of twenty five.

It was to be implemented into twenty IBM countries including Japan, Australia and Canada.

It was the system that calculated prices for IBM products.

I started software development in nineteen eighty two as an eighteen year old trainee.

I was the best trainee who ever came into IBM in terms of work delivered and then promotions and pay-rises.

I was the “rising star” in IBM Australia’s IT shop.

A lot of older guys actually protested my promotion to be the System Architect for that project in January nineteen eighty nine.

Even so, in nineteen ninety, my transition year, I had to go to “IBM System Engineering School” and start with the trainees.

For each class this included having to master manuals in the region of three thousand pages.

We would have an entry exam on the three thousand pages of manuals where you had to get seventy percent or get kicked out.

We then did three weeks of extremely intense “school” where about thirty percent of the students dropped out and resigned from IBM.

Their response was usually along the lines of.

Quote.

I did not realize this is what I signed up for at IBM, I am out.

End quote.

The failure rate was much higher for the ladies.

Many of the ladies would simply break down and cry realizing that they would never be able to do the job they had dreamed of.

For some reason the ladies who wanted to be IBM Systems Engineers did not realize that they would not simply be passed through the system as quota women.

Making sure IBM computers ran faultlessly was still considered important at IBM in nineteen ninety.

I did midrange school and large systems school.

This was despite having never even seen an AS four hundred at the time.

I had the great advantage of having a photographic memory.

In my midrange entry exam I only got seventy two percent.

That is how hard these exams were.

I got one hundred percent on the mainframe entry exam.

Trainees then did months of branch work understudying to your mentor before you would be allowed to even speak to a customer.

That would get you to “associate” level in 2 years as a new hire.

I was fast tracked to “associate” level.

Then I had to spend nineteen ninety two and nineteen ninety three working as an “associate” before I was finally promoted to full “engineer” level in December nineteen ninety three for my efforts that year.

As an IBM Systems Engineer it was your job to help the customers configure the IBM hardware and software for maximum performance so that their investment in our hardware gained the maximum return on that investment.

I note that reliability was not considered a factor in as much as our mainframes were expected to be one hundred percent reliable.

Just like an airplane.

It was a very tough and demanding job.

It was FAR harder than just being the youngest System Architect in the country running a four million US dollar four hundred work month development project at the age of twenty five.

The expectations and hours were off the charts.

Less than half the people who started ever made it to Associate level. They left for less stressful jobs.

I made a comment just today that in nineteen ninety three I was getting home from work at around one in the morning.

I would put on my jogging gear and go for a one hour jog in my neighborhood to get some exercise.

Then I would make myself a sandwich and have a shower and get to bed around three in the morning.

Then I would get up at six in the morning and do it all again.

That was the only time I could find to go and get my exercise to keep up my energy and well being.

That is what it was like some times to be an IBM Systems Engineer.

Mistakes could end your career at IBM as a Systems Engineer.

Please allow me to give you an example.

In my very first IBM customer account I made a mistake.

This was in April nineteen ninety one.

I put some software on the development mainframe that talked to DB two.

But the communications controllers that we attached our data analysis server to were attached to the production mainframe.

So the development mainframe had to send data via the production mainframe to the DB 2 gateway on a Local Area Network server.

There is a parameter on the development mainframe in the Virtual Telecommunications Access Method software called V PACING.

This parameter defaults to zero.

This parameter had to be set to one or the production mainframe would crash.

There was no mention of this parameter in the manuals for the software I was implementing.

So I did not make the change.

As an IBM systems engineer one of the rules was that you do not change any configuration parameter unless you knew that it had to be changed.

My mistake had the effect of crashing the production mainframe, twice, within an hour.

I had to go through a very detailed investigation and then a tribunal hearing organized by the customer.

The customer System Network Architect expert testified on my behalf.

He said that there was no mention that this parameter must be set to one in any manual that I could reasonably be expected to have read.

He testified that even a man with five years experience in communications software might have made the same mistake.

He recommended to the tribunal that I should be found guilty of causing the outages, but that I should not be punished in any way as there was no way for me to know I was making a mistake.

If his opinion had been otherwise I would have lost my job.

I had a wife and three children to feed at that time and there was a recession.

So I was very thankful for this mans honest testimony.

That is what it looked like to be an “IBM Systems Engineer” at that time.

One mistake could end your career.

You were held accountable for everything you did.

How many self described data engineers would accept that their products must have one hundred percent up time and that any mistake in the products or any outages in the availability of their products would result in their termination without a reference?

None.

Absolutely none.

This is an opinion piece.

My opinion is this.

No man should use the word Engineer in his professional biography unless he is willing to be punished by losing his job, without a reference, if he makes a mistake that he should not have made and could have avoided with more careful application of his skills.

If a man is not willing to be terminated from his job after being found guilty of making a mistake he could have avoided by an internal tribunal?

He is no engineer.

He is something else.

Perhaps he is a programmer.

Perhaps he is an administrator.

But he is not an engineer.

Not even close.

That is my opinion.

If you have a different opinion?

You know what the comments section is for as well as I do.

Please feel free to share your opinions in the comments section.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

IBI Downloads

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The post IBI-063-Data Engineering appeared first on Instant BI.

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello and welcome Gentlemen.

There has been an interesting debate on X recently about how few jobs have gone to white men in the US over the last four years.

As everyone knows, we have had affirmative action quota women for fifty years.

This is not a new phenomenon.

So.

My open offer to the marketplace in the United States is as follows.

If you are a white man?

If you have an I Q of one hundred and thirty or more?

If you would like to make a lot of money in the data warehousing business?

If you would like to make a lot of money in the business intelligence business?

Then please review my freebies document.

Get Freebies

Please review the links that it points to.

Then.

If you would like to make a lot of money in the data warehousing or business intelligence business?

Then come and join me in creating the world’s leading data warehousing and business intelligence business.

How do I know we can do this?

I was one of the worlds top data warehousing consultants in 2010 when I was woke cancelled.

I have endured fourteen years of woke cancellation for the crime of saving men’s lives.

I know how to build the worlds leading business intelligence and data warehousing business.

All I need to do is to break out of my woke cancellation.

I am sick and tired of the fifty years of affirmative action quota women that we have had.

I am sick and tired of women of far lesser skill being given jobs over better qualified men.

I am sick and tired of hiring being based on affirmative action or so called positive discrimination.

I propose that in Instant Business Intelligence we will have a culture of business partners based on merit.

I propose that we denounce and kill off affirmative action and so called positive discrimination.

I am going to start this process with high IQ white men.

High IQ white men can join me in this effort as business partners.

You will be able to sell your customers the service that they can sustainably increase their profit over time.

If a company wants to hire an affirmative action quota woman to try and sustainably increase profit and they fail?

That is a good result for us.

The more companies that realise that their human resources department is a cost centre dragging down profit?

The more companies that realise that they have large numbers of affirmative action quota women who were hired by their woke human resources department?

The more money we will make.

We will offer our customers the services of high IQ men, some white, some black, some red, some yellow.

And some will even be pink men with purple polka dots.

I do not care what the colour of a man’s skin is.

I care about how good he is at his job.

Period.

So.

I will get this revolution started with high IQ white men.

If someone wants to call me a sexist or a racist for promoting high IQ white men?

Then so be it.

I have been falsely called a paedophile for fourteen years.

A few years of being called a sexist and a racist is fine by me.

I am 61 so I will only have to put up with a few more years of name calling.

Now.

In summary.

If you would like to consider joining me in the world of Instant Business Intelligence?

Download my freebies link.

Review all the contents.

And make your own decision as to whether you want to join me.

The deal will be this.

You can apply for a non exclusive franchise, United States wide.

This means that you can promote my free, and paid, products to any company in the United States.

We will not have “territories” for Instant Business Intelligence business partners.

It will be a “free for all” as far as territories go.

I will be the sole arbiter for disputes for all Instant Business Intelligence business partners.

Now.

I just want to make one other point clear.

I do have business partners who have their own branded versions of my software.

These products are substantially more advanced than the free Instant Business Intelligence versions of these products.

These partners have territories.

These partners operate independently.

They have paid versions of my software and get priority in support.

They sell their own versions of my software.

If you would like to have your own branded versions of my products?

You can discuss this with me at your leisure.

And with that?

I hope you found this blog post interesting and informative.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

IBI Downloads

IBI Videos

Carphone Warehouse Reference Video:

The post IBI-060-Open Letter White Disenfranchised Men appeared first on Instant BI.

Original Post

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello Gentlemen.

This week I became aware that these data boot camps that are being offered on the internet have prices ranging from 10,000 dollars to 20,000 dollars.

At least those are the prices I became aware of. If anyone has any other information I would be happy to hear.

I had thought they were being offered for around 500 dollars, and even that I would argue is too much.

Having thought on this a few days I thought I would put up an Article on this matter.

Firstly, please allow me to say that these sort of “boot camps” are not how you become great at your job.

And they are most certainly not going to give you what you need to break into a profession and get a job.

This is why I thought they were being offered for around 500 dollars.

I would warn anyone considering buying a boot camp to very seriously consider whether that is the best investment for their money.

So that you know what good education looks like.

On the link below you can go and review the Digital Altitude RISE course to start a business.

This, along with the more basic start up course, and membership of the groups, plus a reselling license for 25% commission, cost two thousand dollars in 2017.

That is what two thousand dollars of training looks like.

One of the most important aspects being that if you resell it you can get your money back.

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So please allow me to share with you the most reliable path to become great at your profession by using myself as a good example.

I will go back to my grand mothers who, when I was a very small boy, would tell me.

“Your mummy works very hard for you making you nice food to eat, keeping your clothes clean, making your bed for you, washing your sheets for you. So you must always find a way to make your self useful for your mummy.”

This made sense to me.

So, by the time I was four I was able to iron the handkerchiefs and tea towels.

I would follow mum around the house reading the newspaper to her while she was doing her chores.

Of course, I had a very limited vocabulary, so every time I came to a word I did not know I would spell it out and mum would tell me how to say the word, and then what it meant.

This is how I first started gaining my vocabulary. Reading the newspaper to my mum to save her time in her busy day.

But, of course, being a little boy, I wanted to be helpful to men.

My uncle was a builder and his son was the same age as me. So one day, when I was 5, I asked him if I could go to work with him and please help him at his job. He said no because I did not know enough to be helpful. He told me I needed to be finished kindergarten before he would let me onto a building lot.

My first day on a building lot I was so excited I was bouncing around like a jumping bean.

I was with my cousin, his son, and we were told to stand a good distance away from the building site and the men went to work. My uncle would yell out the name of the tool he was using and the other men, when they changed tools, would yell out the name of the tool they were using.

This was so we could learn what the tools were. Soon I knew the difference between a claw hammer and a ball hammer. Soon I knew the difference between a fixed set square and an adjustable set square. And so on.

After a few months of this we were given our very first “jobs”. When one of the men needed a tool that was in his truck, he would call out to us to fetch the tool from his truck and bring it to the edge of the building site. We were not allowed on the site itself when we were 6.

In this way we learned the names of all the tools and what they looked like. We learned where each builder kept his tools in his own truck.

Later on, my uncle worked in a transportable home production company and there were lots more tools and lots more men. We ran around getting their tools for them and watching what they were doing.

At the factory there was a big wall where hundreds of tools hung for ready access. And there was also a big “tool room” with rows and rows of shelves and hanging space for tools. When the men finished work they would have a few beers and a few cigarettes to wind down. And my cousin and I would clean the tools and put them into their correct positions for the next days work.

All through this time we would be taught valuable lessons by the men.

I recall one time, when I was six, my uncles power drill either broke or stopped working for some reason. So we went to the hardware store to buy a new power drill. I saw that the power drill he bought was much more expensive than another power drill just next to it. So, being a curious child, I asked him why. His response stuck with me for my lifetime.

“A tradesman is only as good as his tools. You are always better off to buy the best tools.”

I am 6, he is ancient and can build houses. So, I am going to believe him.

Across my childhood I worked for my uncle on building sites. At one stage he built seven homes in seven years and I laboured on the homes as much as I could, to learn as much as I could. I would have a home one day and these lessons may well come in handy. It turned out that happened.

Now, I have put these comments here to make a point.

There is an experiment called “The Five Monkeys Experiment”.

This short video shows you an animation of the theme. It’s worth watching.

The Five Monkeys Experiment

We have the saying “Monkey see Monkey Do” for a reason. Even among monkeys the basis of all learning is “monkey see monkey do”. We are no different. Since we were primates we learned by “monkey see, monkey do”.

Even when mankind was hunter gatherers we can be certain that lessons were passed down by “monkey see, monkey do”.

In the trades we have a name for this, it is called Master and Apprentice. For at least the last ten thousand years, the primary way of passing along knowledge has been by the mechanism of Master and Apprentice. And that is what I was doing when I was helping my uncle. I was acting as an apprentice, though, of course, a very basic apprentice.

Both his sons apprenticed to him with the plan to get their builders licenses. Sadly, his son who was my age died in a car accident at the age of 19.

The relationship of Master and Apprentice has been how knowledge has been passed along for millennia. Sure, you can read books. We call this being “book smart”. But reading books is no substitute for the Master Apprentice relationship.

This is why, when I was graduating high school, I applied for more than 100 apprenticeships. I turned down the offer of the most prestigious scholarship in Physics in the country. I knew that doing an apprenticeship would stand me in much better stead to break into a good profession than would doing the most prestigious Physics course in Australia.

In the area of programming an apprenticeship is actually called a traineeship to differentiate it from the labour style of master apprentice relationship. There is no physical labour for trainees as there is with apprentices.

I started my traineeship on January 18th 1982 and I had the opportunity to learn from some very smart men. I took that opportunity and listened and learned as actively as I had when I was a six year old finding out the difference between a claw hammer and a ball hammer for the first time.

For example? What is the difference in passing a pointer by reference, versus passing a pointer by value?

The work I did in my traineeship was light years ahead of what we were being taught in University. In my final year at university our team were the only team to be awarded High Distinctions because our software project, an enrolment system for the university, was so far superior to anything else any of the other graduates did.

I felt sorry for the graduates who had just done university because after three years their level of knowledge compared to mine was pitiful. I had made the right decision going for the traineeship over a full time university position on a scholarship.

My next move was to IBM Australia’s international development lab. Here I understudied to a man named Brian Kent who was recognised as the number one System Architect in the country. Brian did not want me to be on the project as a trainee. He wanted me gone. But I worked very hard and proved that I could make a decent contribution even as a trainee.

As much as Brian did not like me? The lessons he taught me were invaluable in my career. I have been for ever grateful to have been able to work with him.

Next, I went to IBM Marketing.  I did my very first data warehousing project in 1991 implementing metaphors data interpretation system. The data interpretation system is now simply called Meta five and I will use that name for the remainder of this article.

I built a third normal form database which was a terrible mistake. I independently invented the idea of multi-level summary tables and that worked to get the sale made and to help my customer make more money.

The meta five software had so many features that we really didn’t know how to use it. So we invited Steve Gordon to come to Australia and help teach us. Steve was a master and a couple of us were his apprentices.

Once we had figured out how to actually use Meta five we found out that dimensional models were a good idea. However, the skills to develop and deploy dimensional models were considered IBM Confidential and I was not allowed to be trained on these things.

In 1992 it was a terrible year in IBM Australia in terms of revenues. At the beginning of 1993 I asked if there could be a budget made available for me to attend the Metaphor Global Users Conference in San Francisco scheduled for September. My manager told me absolutely not. She said that if I wanted to go to the conference then I had two choices. One, I could pay for it out of my own pocket and take annual leave to attend. Or I could bill other IBM Countries during my annual leave allocation, and money earned from those billings could be put aside in an account to go to the conference.

So that year I had to do with no annual leave, and I had to work outside Australia to earn the billings. And I had to meet all my targets inside Australia as well. That’s how I got to go to the Metaphor Users Conference in 1993.

When I was there I heard all sorts of amazing presentations by massive companies like Coca Cola, Wallgreens, Better Homes and Gardens, Proctor and Gamble. NYNEX, a New York Telephone company won the award for most verifiable profit made from Meta five. The manager of the project told the audience that his team were being offered budget they could not spend, and were turning down budget offered by the senior management team.

He said, “Metaphor is such a printing press for money that our management are throwing money at us and telling us to make more money to such an extent we can’t even spend it effectively. We have turned down millions of dollars of budget offers”.

Of course, this is the exact opposite of what most of us are doing. Most of us are presenting proposals to senior management teams or boards and begging for the budget to be allocated. The idea a senior management team would be offering me millions of dollars in budget that I can’t even possibly use over and above the budget I have? Now THAT was a situation I would like to be in.

And, as the story goes, there was this guy who spoke really fast and drew pictures really fast who was the key note speaker that year. The day before I was invited to sit at the table with the Global Head of Coca Cola Business Intelligence. He told us all to make sure we got front row seats for the guest speaker whom he had personally invited.

Who was that guest speaker? That was one Bill Inmon. We remain friends to this day.

I had taken my IBM Customer to the conference, one Colin Stewart. He too was amazed at what he saw. When we went back to Australia we developed a joint proposal to do pure research into building dimensional data models. All these big companies had dimensional data models and we wanted to go in that direction. However, Metaphor would not allow me to be trained in this area so we had to do our own pure research.

The sponsor of the research asked us if we knew anyone at Metaphor he might be able to hire and bring to Australia to help short cut the research. While I was there I had introduced myself to the man Ralph Kimball trained and left in charge in 1989 when he left. We will call him Fred here. So I told the project sponsor about Fred and he agreed to pay the bill to bring Fred to come out and design our base models. I can assure you that was an eye watering bill.

Fred and I remain good friends to this day. He brought me up to speed on the basics of dimensional modelling. And because he was pals with Ralph he introduced me to Ralph via email. That is how I came to be pals with Ralph Kimball. Ralphs apprentice introduced him to me.

I later went to work for Price Waterhouse Coopers where Fred was running the global data warehouse practice from the point of view of models. Fred wrote the Price Waterhouse Coopers data warehousing methodology. And between us we worked out the standards for Price Waterhouse Coopers models.

In 2000 a pal of mine from Price Waterhouse Coopers told me that I just HAD to come and work for Sean Kelly selling the Sybase Industry Warehouse Studio data models.  By this time Sean Kelly was known as “The Bill Inmon of Europe”. I could not make it until February 2001.

My whole team and I were made redundant from Informix at the end of 2000 as part of their cost reductions. So I was able to relocate to Dublin Ireland in February 2001, to start my time working for Sean Kelly. I went to the training class and in walked this old guy, quite a short and well rounded guy, looking rather like one of the seven dwarves in fact. He introduced himself and I had never heard his name.  No one had mentioned his name in the lead up to my move to Ireland. We will also call him Fred here because the reason I didn’t know his name is that he does not like the limelight.

So the class starts and Fred teaches us the Sybase IWS data models. He teaches profiles and I am stunned because I just spent five years trying to solve the problems profiles solve. So I ask Fred “who invented profiles” and he says “I did”.

So I said, “I thought Sean designed the IWS Models”. And he says “No, I did.”

And just like that, I realised I was in the room with the number one data modeler in the world. We became fast friends. He and his family lived just around the corner from us in Dublin. Even though he was an older gentlemen his wife and children were the same age as Jennifer and our children. So they became fast friends while Fred and I were out on the road working.

I actually had the absolute honour of working with Fred on a project in the US for a couple of weeks in 2002. He was bored and asked if he could come over and help me out. Of course I said yes. As he was drawing diagrams on the white board for how we could solve problems I knew I was seeing the mind of God in action. Fred is the smartest man I have ever met and ever worked with. It was a truly humbling experience. I can never be Fred. I can only do my best.

So Fred and I still remain in touch, though he likes to keep to himself nowadays.

In that class for the Sybase Industry Warehouse Studio models I knew my friend was right. I literally HAD to come and work for Sean Kelly to gain access to those models and implement them.

I did a whole string of installations. Lindorf Financial in Norway. New Jersey Media Group in the USA where I designed the new Media Models in a joint development project. Next was Saudi Telecom, Mobily Telecom Saudi Arabia and Orange Telecom in Romania. A part of my job was to train the local Sybase resellers staff so they could sell and implement the second and later projects in their country.

SAP bought Sybase in 2006. Sean Kelly discussed this with Sybase. He was given permission to create new models as long as we did not compete with SAP. So Sean Kelly and I decided to build new telco models and sell them in the marketplace. We sold Carphone Warehouse in 2008 and Sky Talk in 2010 in the UK. This was before I was doxed and slandered in late 2010. Sean was diagnosed with cancer not long after and retired from working. He passed away in 2012 may he rest in peace.

All that story and all that writing is to say this.

If you want to be great in your profession, no matter what that profession is?

You find the masters of your profession and you go and work for them.

Whether that be as a 6 year old boy working for your uncle on a building site fetching different tools?

Or whether that be implementing the data models developed by the worlds number one data model developer.

You find the masters of your profession and you go and you work for them in a master apprentice relationship.

Early on you do it for very little money because you will make your real money later on.

In my first year working in 1982 I was on 7,696 Australian dollars. I made over 400,000 Australian dollars in 2006.  In US dollars my 2006 income was just over three hundred and thirty thousands dollars.

In my 4 years at BHP and my 8 and a half years at IBM, I never once asked for a pay rise. At BHP your salary was set. At IBM I asked my managers to please pay me what they think I am worth. I was consistently paid significantly more than my peers at IBM.

If I can go from 7,696 Australian dollars in 1982, all the way up to 330,000 US dollars by 2006, it’s probably worth listening to my advice.

The only reason I was not able to translate the success of Sean Kelly and I in the 2008 to 2010 period was because I decided to defend the rights of men and boys in keeping a promise I made to my grand father when I was a lad. I did not have to keep that promise. I chose to keep that promise because when I see my grand father again he is going to tell me how proud he is of me that I kept my promise.

You could offer me a trillion dollars. I would not take it if it meant my grand father would not be proud of me when we meet again.

Well, gentlemen, that is my two cents worth on how to be great at your job.

Find a master and go and work for him.

Don’t go to boot camps.

Don’t try and learn to be a master by reading “my top 5 tips for x y z”.

Find a master and go and work for him if you can.

Failing that? Read the books the masters produce.

And gentlemen?

Sadly, right now, I don’t have any jobs on offer because it’s very hard to make sales when you are the second most slandered man in the world. In 2016 I was the most slandered man in the world. When Donald Trump came down the escalator he overtook me!

And with that gentlemen?

I hope you found this blog post funny and interesting.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

IBI Downloads

IBI Videos

Carphone Warehouse Reference Video:

The post IBI-052-How To Become Great In Your Profession appeared first on Instant BI.

Hello and Welcome.

I am Esther.

I am Peters A I Assistant to create voice overs.

I will simply read Peters blog posts, so that you have a choice of reading the blog post, or listening to my voice.

Hello Gentlemen.

Today, I want to share a very funny story with you, if you have about 10 minutes to spare.

No, not Taylor Swifts song moaning about how her boyfriend dropped her.

This funny story is about how I learned to be honest.

I am sure you will like the punchline.

So here we go.

Little boys do not know how to be honest.

We have to be taught.

We are usually taught by our mothers.

So, in 1967, when I was 3, my mum decided it was time to teach little Peter to be honest.

This is how she did it.

She put a bowl of bananas on the kitchen bench and told me not to eat any bananas without her permission.

She said taking a banana without her permission was “stealing”.

Now, where I grew up in Wagga Wagga Australia, bananas were very expensive and only available in season.

AND they were my favourite food.

So, we all know what happened next.

When mum was not looking I “stole” a banana, ate it, and put the skin in the bin.

I didn’t even know what “counting” was, so I was pretty easily caught.

Once I realised my mum could count the number of bananas in the bowl, I would steal the banana from the bunch in the fridge.

I soon realised mum was also checking the garbage tin in the house and outside.

So I started hiding the banana skins under the house.

That’s what 3 year old boys do.

We are quite ingenious about stealing our favourite food.

This went on for a while.

Then my mum gave me the lecture.

She told me that stealing the banana was wrong, and I knew it, because I was hiding the skins.

So, from now on the rules would be as follows.

1. If you steal a banana, and you come to me and admit it before I find out, you get one smack.

2. If you steal a banana, and I have to ask you about it and you admit it when I ask, you get two smacks.

3. But if you steal a banana, and I ask you about it and you lie to me to get away with it? You get four smacks.

Of course, mum was teaching me that lying was worse than stealing the banana.

In those days, when I was 3, the smacks were quite light.

And then banana season ended.

Six months later mum started it all again.

Strangely, the smacks seemed much harder.

But, of course, I kept stealing bananas, and I kept lying about stealing them.

Four smacks for a banana?

I was taking that deal.

Soon mum stepped the “smacks” up to be a smack with a big wooden spoon that was about 3 feet long.

I had seen her hit my bothers on their bare bottoms with this spoon, and it looked like it really hurt.

Well? It did!

Now I had a problem.

I really loved bananas, but four smacks with the “wooden spoon” was too high a price to pay.

So, I started stealing the bananas and admitting it to mum, and taking the one smack with the “wooden spoon”.

But pretty soon?

That one smack was so hard that even then I was discouraged.

But I still kept up stealing the bananas.

I really liked bananas!

Then one day my mum says to me.

“Peter, mummies have magic powers. We can read the thoughts of our children. God gives us this magic power to help keep you safe.”

Oh? So mummies have magic powers?

That is how she knows I am lying?

She could have told me that sooner!

Then, just to be sure, I tested out “mummies magic powers”.

Believe me, every time I stole a banana and tried to deny it?

She knew!

Eventually, because “mummies have magic powers to read my mind”, I gave up.

I decided that it was just easier to be honest.

Those spankings with the “wooden spoon” were now so painful they actually made me cry.

It really hurt.

So, all in all?

I decided it is just better to be honest, because “mummies magic powers” will only catch me out anyway.

Fast forward to February 2008.

My mother was dying from Dementia.

I spent the month with her, we talked about life, the universe, and everything.

This was likely the last time I would get to talk with her, and it was lovely.

At one point she said to me.

“Peter, I want you to know I am so proud of you that you are an honest man”.

I laughed at her and said.

“Well it’s hard to be dishonest with you as a mother.”

She asked.

“Why do you say that?”

And even as I said the words I knew how ridiculous they were.

I said.

“Well, you had magic powers to read my mind so I simply decided it was better to be honest.”

Mum laughed and asked me what I meant.

I said.

“Do you remember, when I was a little boy, you told me mothers had magic powers given to them by God, to read the minds of their children, to keep them safe?”

She said.

“Yes, I do remember telling you that.”

I said.

“Well, I believed you, and it stuck with me all my life. You are why I am honest.”

She laughed and she laughed and she laughed.

It was so lovely to see her laughing in her demented state.

Finally, she stopped laughing and she said to me.

“Peter, when you tried to lie to me, you put your left hand over your bottom, because you knew the spanking was coming.”

We both laughed & laughed at the thought of me, as a little boy putting my left hand over my bottom & saying.

“I promise mummy, I didn’t eat the banana!”

As I grew up I had other people in my life who influenced me greatly.

None more so than my Grandfather, who was a world war two veteran.

Honesty.

Honour.

Integrity.

These were the three words that these people drummed into my head.

They said.

“Above all else, grow up to be an honest man of honour and integrity.”

And so I did.

In business, I resigned three good jobs when I was asked to do something, that I felt conflicted with my own personal ethics.

In Australia, in the nineties, it was very well known that I resigned from those three jobs on ethical grounds.

As a result?

In business, I have had men give me multi-million dollar deals, on my handshake and my word, that I WILL deliver the project I am selling them.

Today, when young men ask me, what would I say are some of the reasons I have been so successful in life?

I always tell them the basis for everything I do is honesty, honour and integrity.

I tell them on top of that you have to add hard work.

I tell them it’s not easy.

I tell them life is much easier, in the moment, to be a liar.

But to lie comes at the price of your own self respect.

I tell young men, that if you can not respect your self enough to be honest?

Then don’t expect any other man to respect you either.

Honesty, Honour and Integrity, are the basis on which I built my life.

Everything else is built on that foundation.

That foundation must be rock solid.

Now that I have turned sixty?

I am very proud of the life I have lived.

When I see my grandfather again?

He is going to shake my hand, pat me on the back, and say, job well done.

I am looking forward to that day.

Sadly, many men have chosen not to be honest men of honour and integrity.

We see the consequences of this all around us.

So.

If you consider your self an honest man of honour and integrity?

Please feel free to add your thoughts and comments below.

Let us show the young men what honest men of honour and integrity look like.

Perhaps they will follow our example.

Perhaps they will not.

But, in my humble opinion, it’s worth setting the example publicly.

Thank you in advance, for all those men who comment, and set the example, for the younger men.

And with that?

I hope you found this blog post funny and interesting.

Thank you very much for your time and attention.

I really appreciate that.

Best Regards.

Esther.

Peters A I Assistant.

IBI Downloads

IBI Videos

Carphone Warehouse Reference Video:

The post IBI-051-How Did Peter Learn To Be Honest appeared first on Instant BI.