A conversation with the father of the data warehouse, Bill Inmon

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This is a podcast episode titled, A conversation with the father of the data warehouse, Bill Inmon. The summary for this episode is: <p>Those who don’t know their history are doomed to repeat it. If there is someone who can speak to data history, it’s <a href="https://www.linkedin.com/in/ACoAAAFdHasBHDFkg4JIK2YHXHaKCY9Wt5xvqiI" rel="noopener noreferrer" target="_blank">Bill Inmon</a>. How did data warehouses start? Why is the computing profession still immature?</p><p><br></p><p>Join <a href="https://www.linkedin.com/in/ACoAAAGdvh8ByUbpFlcE0mITvhxT-ivo0l_mzOM" rel="noopener noreferrer" target="_blank">Tim Gasper</a>, <a href="https://www.linkedin.com/in/ACoAAAE_pWMBR7k60w6xpXEoAiARb9omer0qUaQ" rel="noopener noreferrer" target="_blank">Juan Sequeda</a> and Bill Inmon, the father of the data warehouse and Founder of <a href="https://www.linkedin.com/company/forestrim/" rel="noopener noreferrer" target="_blank">Forest Rim Technology</a>, to learn about the past and present of data, and where things might be heading in the future.&nbsp;</p><p><br></p><p>Key Takeaways</p><ul><li>[00:05&nbsp;-&nbsp;01:00] Introduction to the Father of the data warehouse, Bill Inmon</li><li>[01:11&nbsp;-&nbsp;02:28] Cocktails &amp; Cheers</li><li>[02:31&nbsp;-&nbsp;03:33] What actor would you cast for yourself?</li><li>[03:39&nbsp;-&nbsp;06:47] Running in circles in the data world, a result of the profession's maturity</li><li>[06:49&nbsp;-&nbsp;10:20] Bill's recent post about loyalty to technology versus loyalty to business</li><li>[10:22&nbsp;-&nbsp;12:58] Specialists in computer technology, how programming has changed over time</li><li>[13:06&nbsp;-&nbsp;15:08] Continuing education and certifications with programming paths</li><li>[15:10&nbsp;-&nbsp;24:40] The history of computing: from army, to mafia, to your pocket</li><li>[24:40&nbsp;-&nbsp;32:22] Key moments and milestones Bill has observed throughout his career in networking</li><li>[32:28&nbsp;-&nbsp;33:59] Understanding the customer and looking after them</li><li>[33:53&nbsp;-&nbsp;38:00] Microsoft Chatbot</li><li>[38:00&nbsp;-&nbsp;41:04] A solution in search of a problem, showing business value</li><li>[41:10&nbsp;-&nbsp;43:41] The Inmon and Kimball approaches</li><li>[43:58&nbsp;-&nbsp;45:50] What's next for Bill?</li><li>[46:11&nbsp;-&nbsp;58:46] Lightning round</li><li>[58:53&nbsp;-&nbsp;01:04:16] Takeaways</li></ul>
Introduction to the Father of the data warehouse, Bill Inmon
00:54 MIN
Cocktails & Cheers
01:16 MIN
What actor would you cast for yourself?
01:01 MIN
Running in circles in the data world, a result of the profession's maturity
03:07 MIN
Bill's recent post about loyalty to technology versus loyalty to business
03:30 MIN
Specialists in computer technology, how programming has changed over time
02:36 MIN
Continuing education and certifications with programming paths
02:02 MIN
The history of computing: from army, to mafia, to your pocket
09:29 MIN
Key moments and milestones Bill has observed throughout his career in networking
07:42 MIN
Understanding the customer and looking after them
01:30 MIN
Microsoft Chatbot
04:06 MIN
A solution in search of a problem, showing business value
03:04 MIN
The Inmon and Kimball approaches
02:30 MIN
What's next for Bill?
01:51 MIN
Lightning round
12:34 MIN
05:22 MIN
Advice on data, life, and who the next guest should be
02:30 MIN

Speaker 1: This is Catalog& Cocktails, presented by data. world.

Tim Gasper: Hello, hello, hello everyone. It's time once again for Catalog& Cocktails, presented by data. world, the data catalog for agile data governance, to give power to people and data. We're coming to you live from Austen, Texas, it's an honest, no BS, non- salesy conversation about enterprise data management, with tasty beverages in our hands. I'm Tim Gasper, longtime product guy and data nerd here at data. world, joined by Juan.

Juan Sequeda: Hey, Tim. I'm Juan Sequeda, I'm the scientist guy here at data. world, and it is a pleasure to be back. Season five, 2023, I've lost count at 115 episodes or whatever. And today our first guest at this season five is the one and only Bill Inmon, the father of the data warehouse of legend, who has seen so many things over so many decades. Bill, it is such a privilege and honor to have you as our guest. How are you doing, Bill?

Bill Inmon: I'm doing fine Juan, how are you doing?

Juan Sequeda: We're doing great. Super excited for you to be here. But let's first kick it off, telling toast. What are we drinking and what are we toasting for?

Bill Inmon: Well, it's a new year, we're all alive, and progressing forward. And when you get to be my age, that's something that you don't take for granted.

Juan Sequeda: I'll definitely cheers to that. How about you, Tim? What are you drinking, what are you toasting for?

Tim Gasper: I'll also cheers to 2023 being safe and well, and probably a little warmer over here in Austen than for you, Bill, in Denver. But cheers to 2023, and I am drinking a scotch old- fashioned, I thought I would keep it kind of smoky and classy and gets the job done, just like a good data warehouse should, so...

Juan Sequeda: And I'm going to start calling these just Mexican old-fashioneds. It's a slide, it's agave with some orange bitters and just some bourbon in here. And I'm going to be toasting for just 2023 kicking off, and all the exciting events and conferences. My first conference is going to be in a couple weeks here in Austen, Data Day Texas, where Bill is also going to be there. Really excited that we'll be able to go hang out again Bill, so cheers to that, cheers to 2023, cheers.

Tim Gasper: Cheers.

Bill Inmon: Cheers.

Juan Sequeda: So, we've got our funny question of today, which is in a movie about the history of the data warehouse, who would you cast to play the role of yourself, Bill?

Bill Inmon: Well, there's really no question about it, there's really only one actor alive, and that would be Brad Pitt.

Juan Sequeda: I can see this, I can see this happening.

Tim Gasper: I can see it too. It was either Brad Pitt, or Tom Hanks, or maybe Tom Cruise, any one of them I think would do a great job for you.

Juan Sequeda: You took the Tom Cruise. I was going to say Tom Cruise, but it has to be kind of for Tom Cruise. But I was also thinking like Clint Eastwood, I think.

Tim Gasper: I could see that too, yeah, yeah.

Juan Sequeda: How about you, Tim?

Tim Gasper: To play myself, you know I always go with Keanu Reeves, he's the guy who I go to. I'm a fan of The Matrix, and I enjoy his recent movies. Hopefully he would present me as a really cool nerd.

Juan Sequeda: All right, well look, there's so much to talk about, and I think Bill, we can definitely talk for days and days so let's just kick this off. So honest, no BS, why does it feel that we're going in circles in the data world? Like, why don't we get the problems today? The problems that we see today are the same freaking problems that we were seeing 30 years ago and so forth. Why, why are we still in this problem? We're in circles.

Bill Inmon: First of all, there's lots of reasons for it, there's no one reason for it. But there's one main reason, and that is that our profession, the profession of IT, is an immature profession. Our profession is maturing. If you compare IT to other profession, it's no contest. IT has been around, it depends when you start to measure it, since about 1960. But if you go back to Egypt, you find that on the walls of the pyramids you have accountants talking about how much grain is owed the Pharaoh. If you go to Rome, you find walls of Rome that were built by an engineer 2, 000 years ago. If you go to South America in Chile, you go into caves in Chile and they've found evidence from bones in Chile that medicine has been practiced as long as 10,000 years ago. So when you compare 10,000, and 2,000 and, 3 and 4,000 years to a measly 50 or 60 years, it's no contest. You can't argue about it, historically our profession is an immature profession. And what we're finding is, from customers and sales and vendors and everything, the progression has been very fast. But nevertheless, we as a profession are maturing. And a lot of the problems that you find today are really symptoms of the immaturity of our profession.

Tim Gasper: Mm- hmm. Can you go into a little bit more about what we're doing a little incorrectly? Like, what would you say are some signs of the immaturity here?

Bill Inmon: Tim, they are all over us, but I'll give you a couple. Number one is education, is the computer and technology entails education for everybody. Users, programmers, developers, everybody. And yet when you look at education, education is done primarily by reading the marketing that's put out by vendors. And so, wait a minute, and people don't recognize when the vendors put out marketing they are for education, but they're primarily for the benefit of the... They are biased education, and yet people go in and believe that right and left. But there are many, many other indicators of the immaturity of our profession.

Tim Gasper: You wrote a post recently, it was one of the things we discussed before, is about loyalty. And I think this is something that was a big aha moment when we chatted about this, about loyalty to the technology versus loyalty to the business. Can you please expand on this? I think this is something that everybody needs to really understand and acknowledge.

Bill Inmon: Today, people that work in corporations in the de facto work for the technology vendor. Now, in order to understand this, what this means and how this happens, let me go back to the beginning. A long time ago, in 1960, in the beginning of things, it was thought that a programmer and a technician should be paid at the same level as a secretary. And in fact, they were. And when I started my first job out of college, I was paid like a secretary, I made$ 6, 000 a year. And what happened is, very quickly people began to do computation and use computers, and they discovered that technical skills were quite important. So what happened was, as people were working in these corporations they found that it was much easier to get a pay raise and to get an elevation in their career by going to a different company. And so quickly the people began to be loyal to the vendors, because it was the vendors that were the key to long- term advancement and success. And today you find that that attitude still holds true, people think that... I was at a very large corporation just the other day, and the people were no more interested in what the technology's going to do to their corporation. They were interested in getting the new technology on their resume so they could jump ship. If you take a look at the careers of people that are in our profession and find out how many times they've changed jobs, you'd find that the IT profession is not at all like any of the other professions, just because the key to moving up the corporate ladder is not in the corporation, but by an expert in a technology.

Juan Sequeda: And is this a bad thing?

Bill Inmon: I never, ever thought about goodness or badness, I just describe, is it a real thing? Yes. Is it good? I don't know. Is it bad? I don't know, but it's a sign of the immaturity... Our profession is maturing, don't get me wrong. In terms of evolution and maturity we've come a long way, we've still got a long way to go. But our profession is maturing, but in terms of goodness or badness it's kind of like asking me is it good or bad that the sky is blue? Well, I don't know, I don't know. It sounds good, I'm not in charge of the sky. So I really have no comment, is it good or bad? I don't know, that's just the way it is.

Tim Gasper: Mm- hmm, yeah. You know, I find your comment about how programmers started off getting paid the same as secretaries and assistants very interesting, because it kind of fits into this mold that folks really thought that this was going to kind of be a profession like any other that existed, right? And it was like, " Oh yeah, you're a steelworker, I'm a secretary. Oh, you're a programmer right?" But then quickly I think our space kind of evolved to being lots of little niches, of different kinds of technologies. And at least a perception, whether it's a reality or not, but a perception of exclusivity. Like, " Oh, you're a programmer, you're a tech head," or something like that. " You're different, you're different than your sort of average Joe," or something like that. Do you think that that has been a good thing or a bad thing, do you think that changes over time, or do you think that kind of this is just sort of the uniqueness of what... Like not everyone's a doctor, right? Not everyone's going to be a technology specialist.

Bill Inmon: I think it's another sign of the maturity of our profession, that in 1960, which is probably before you were born but that's when I started. In 1960, computers were the magic word, computers. But that meant everything, that meant everything, and in fact my wife and I have discussions about this all the time. She is a doctor and the world of medicine is the same way, that you have doctors that are a specialist in one thing, you have doctors that are a specialist in another thing. You don't want to go to your general practitioner doctor to have an open heart operation, you know? I guess you could, but that wouldn't be a very smart thing. So the world of medicine in their maturity has found that the world of medicine is a wide variety world, there's no one doctor ever that's an expert in all forms of medicine. It simply is not true, doesn't happen. And our profession is heading the same way. When we started we were technicians, we were computer people or whatever we were. Today we are data technicians, we are architecture technicians, we are personal computer technicians, we are program... I mean, we have all these specialties, and that too is another symptom of the maturing of our profession.

Juan Sequeda: This is fascinating, the analogy you put with being general meaning very specific, right? I think-

Bill Inmon: Yep.

Juan Sequeda: ...we're going to see more of these specifications. I wonder, I see in so many different other areas, and it's a sign of maturity, is that people have to get not just degrees and study but they actually have to go through the association and get certified around these things. My wife's a BCBA, a board- certified applied behavior analyst, stuff like that, right? You go to medical school, you get specialized what you study is. Is this something that you foresee that will happen in the computing profession, or not for us?

Bill Inmon: Oh, it's happening right now. I mean, it's alive and well, and it's part of the evolution, our maturation of our profession.

Juan Sequeda: Interesting .

Tim Gasper: That's just fascinating.

Juan Sequeda: But ...,but it's interesting that going back to what you started earlier, that a lot of the education has happened to vendors, and are we going to start seeing these kind of focused certifications and stuff by vendors? I mean, that's what's happening right now. " I got certified by Snowflake to go do this, or by Databricks." But then you're being certified by the technology and not certified by the fundamental principles of the data, and then you end up focusing too much at the technology. It's like a medical professional being, " I do open heart surgery, but no, I can only use these types of tools for it, I can't do these other things." Kind of seems -

Bill Inmon: ....

Juan Sequeda: ... downthat route.

Bill Inmon: That's exactly what's happening, and that's a sign of the immaturity of our profession, that our profession has gone so moved towards vendors and the vendor message that the underlying principles and disciplines have been glossed over or lost completely. And that's exactly what's happening.

Juan Sequeda: Let's talk a little bit about the history, about how did we get here? I mean, I love how we... Let's talk about, we were discussing before the show, like early uses of computers, and how tech managers, how people became managers of this stuff who had no idea. How did Gardiner come to play, and how did the first data warehouses like... Please take us down this journey that you have gone through, because I think this is fascinating. I am a big fan of history, if you don't know your history you're doomed to repeat it, and we're seeing this over and over again. So, please enlighten us.

Bill Inmon: I would be happy to, but I have to warn you if I really did a complete job we'd be here for a week or two. But yes, I am a student of the history of the computer profession, and I think it's very important. Let me tell you a sad little story, I was at a conference a while back and I was among people that are educated, educated people, these are not dumb people. And I mentioned the name Ed Yourdon, and nobody at the table even knew who Ed Yourdon was. And Ed Yourdon is one of the formative pioneers of our profession, our profession has the nasty habit of trying to forget people that have made contributions to our profession. Gene Amdahl, you don't know what computing would be like without Gene Amdahl. And yet people don't even know who Gene Amdahl is, who what he did, what he does. So I'm very interested in the history of our profession. Doing some reading, I wasn't there for these events, but the very first concept of our computer came in a very crude fashion. It came back in India when people were weaving rugs, and people had to have these... Have you ever wondered how these wonderful Indian rugs with all of these intricate designs get to be weaved? They get to be weaved by people that have the punch cards, it was the first punch card. And these punch cards control the machine, and then that idea of being able to use logic to control activity was really probably the original origins of the computer. Mainly the Chinese abacus was, I'm not sure about that. But in terms of the computer as we know it today, there was a gentleman in England named Alan Turing during the World War Two, that cracked the code that was used in Germany. Now he didn't build a computer, but he had the early ideas of how the computers should be built. And so he's probably the first person ever to understand how these mechanical devices in India were able to control machines that build these wonderful rugs. After Alan Turing came along, they actually did start to build a computer. The first computers were built by the US Army, the US Army wanted to build these tables to determine how to shoot their guns more accurately. And that was the first application of computers, and it was strictly mathematical. After that the next organization that found out that they could use this kind of technology was the mafia, the mafia... You're laughing, I'm not joking, I tell you, it was the mafia. The mafia found out that they could use a computer to calculate race track odds, and in doing so they could make more money at the race track. After that the computer was thought to be a device for calculation, and the earliest uses of the computer were strictly for numerical calculation. Then Tomas Watson of IBM made his famous statement, I don't know if he made this statement or not but it's credited to him. He said, " There's a world market for about five computers." Now what he was talking about was a world market for, excuse me one second. What he was talking about was a world market for computational devices, and he was, I don't know if he was right, but he had the right idea. And then one day... And so in the early days of the computer, the computer was thought to be something that was just for running a bunch of numbers and computing. And then somewhere along the line somebody came up with the bright idea, maybe we could use the computer for business, perhaps there is a use for computation in business. And that was a golden moment, because at that moment in time computers hadn't been explored in business. But people then started to bring the computer in and find out, indeed, once you opened up the computer to more than just numbers, once you start to include text and other things that the computer can do wonderful things. Now, when you look at the computation in an abstract form, the computer is fast, it can remember a whole lot, and it can remember accurately. But at the end of the day, the computer is dumb, it's dumb in the sense that you've got to tell it what it's got to do, and if you don't tell it what it's going to do then it can do it fast, but it can't do it well or properly. And so the next advent of the computer was to enter into business, and so the computer entered into business and started to do all kinds of things that were very repetitious, and this greatly alleviated business. And then one day the volumes of data began to accumulate, and we discovered we needed something called a database management system. And so we discovered that with the database management system, that allowed us to extend the range of what can be done. And so that now, before the database management system we had to have a programmer try to do the location, allocation, maintenance, insertion, deletion of data, and that was a very tedious thing to do given what we were asking the computer to do. So the database management system came along and alleviated that burden on the computer. After the database management system came along, we discovered that gee, maybe we could use the computer for even more important things. Maybe we could do something called transaction processing, and to do transaction processing you had to have a new ingredient. You had to have the query and activity that you're doing on the computer done very quickly. And so, however, with transaction processing the computer was opened up to the world, because today we have ATM machines, we have airline reservation systems, we have internal manufacturing control systems, transaction processing systems, became the beasts of burden. And with that, the computer became the partner of business. Prior to that point in time the computer was simply a beast of burden, but with the ability to become active in the day-to- day business of bank teller systems, you can't run a bank today without online transaction processing systems. Sorry, can't be done. And so the ability to do transaction processing systems was the second golden moment, because that's when the computer became the partner in business. And then we start to have other uses of the computer, then we have the personal computer, then we have the internet, then we have... You have today even more important uses. So that is a five- minute description of how we went from shooting bullets accurately to doing bank transactions properly.

Tim Gasper: From Army, to mafia, to your pocket.

Bill Inmon: That's right.

Tim Gasper: Bill, I think it's such an interesting thing to see the arc of computing, and obviously you had an opportunity to see many key milestones and evolutions and really be an architect behind a lot of that. What was some of the key moments around sort of the revolution around the data warehouse? Like, what was the key sort of golden moment that triggered to say like, " Oh, interesting, databases have gotten us so far, but we really need to approach sort of analysis of data especially, but certainly other kinds of workloads as well in a different way." And obviously that sparked all sorts of fun things, Inmon versus Kimball, and all sorts of different things like that right? So what was kind of the golden moment that kind of triggered a lot around the data warehouse?

Bill Inmon: Well, let me tell you. I started programming in 1963, so I've kind of been there from the very beginning. And in the beginning we had all of these applications, and that was that. And then all of a sudden we had database management systems, and people... The theoreticians and the vendors came along and said, " The database should be a single source of data for all processing." Now that sounded like a good idea at the time, and given the applications at the advent of database management and databases, that was a proper thing to say. But that understanding of what a database should be locked people in, it said that, " This data has this purpose and this usage, and no more. And if it has any more, anything else, you're breaking the rules and you're a nasty person to think otherwise."

Tim Gasper: The database, the data structure was like, "This is how it will be used," and it was very fixed.

Bill Inmon: Absolutely. And at the time I happened to be a writer for a journal called Computer World, and I started to express the idea in Computer World that data could be used for more than just what you're locking it up for. And this was very threatening to people, because even writing about it before there was a data warehouse, I have a collection of letters in my office and they're burned in my brain. One of them said that I should not be allowed to speak in public ever again, another said that... You're laughing, what are you laughing about? This is what happened, this is the reaction. People said I'm an anarchist, I'm setting the industry back 25 years.

Juan Sequeda: Wow.

Bill Inmon: And I had other things that are not repeatable on broadcast like this, and the notion that you could even think that there was a different notion of data was anathema. People were very threatened by it.

Juan Sequeda: What year was this?

Bill Inmon: Pardon?

Juan Sequeda: What year was this?

Bill Inmon: Don't ask me hard questions. This was, I don't know, 1970, '71, somewhere-

Juan Sequeda: Wow.

Bill Inmon: ... inthat timeframe. And the vendors went out of their way to... I won't go into the details and which vendor, but the vendors went out of their way to make sure that I would try to be muzzled like a dog. They did not like that I was spreading something that was not in line with what they were saying. But nevertheless I kept thinking about, " Gee, you can use data," and that's when the thought occurred to me. There's transaction data, there's application data, then there's corporate data, and application data is data that supports the application, the enterprise data is there to support the enterprise. Let me tell you the kinds of questions that people couldn't answer in that day and age, simple questions like, how many customers do we have? How many products do we have? How many sales did we make? And you would have big, big corporations not able to answer those questions. So I sat down and I said to myself, " Okay, what does it take to answer those questions?" And in order to answer those questions on an enterprise level, you've got to have an enterprise understanding of data, and that's different from an application understanding of data. So those were the original thoughts behind data warehouse, and the resistance to data warehouse was terrific. The vendors, the technicians, everybody hated data warehouse. The one place where data warehouse was loved and understood was in the marketing organizations of the United States, and I'll tell you the names and stories of how data warehouse came to be. We'd been talking about data warehouse and writing books a long time, and then one day we actually got somebody to try data warehouse. And the person that we got to try it... Person, organization that we got to try data warehouse was somebody called PacTel Cellular in Orange County, California. They're now part of somebody called McCaw Communications, but PacTel Cellular was involved in their own terrific fight for market share. This is when cellular phones were just coming out, and you had all of these cellular telephone companies fighting for market share. And God bless PacTel Cellular, for whatever reason they went out and they tried data warehouse. And guess what? They found out that with data warehouse you can start to actually understand your customer, you can keep your existing customers, and you can get more new customers. And all of a sudden the other cellular companies in the world found out about this, and the management of the other cellular companies went down to their technicians and said, " Hey, we've got to have this thing called data warehouse." And for years and years the technicians had been blasting, and all of a sudden management was saying, " This is what we're going to be doing." And so if it hadn't been for the marketing people in PacTel Cellular I don't know what we'd have done. But then the cellular telephone industry started to adopt data warehouse, and then the next big person to identify it and use it, and it was in his own book, was Sam Walton of Walmart. And let me tell you, once cellular telephone companies and Walmart started to adopt data warehouse, that was the end of the game. That data warehouse was now going into the world as a full- fledged concept, kicking and screaming. IBM, Oracle, Microsoft, SEP, were no help at all, their management fought it tooth and nail.

Juan Sequeda: Oh. So again, this is fascinating, fascinating history right here. And what I love is that the big aha moment was not the tech side, it was the marketing, it was the non- tech people who they wanted to go understand the customers so they can sell more to them, go acquire market share, keep them and so forth. So I mean, this is kind of this era, I feel that we're in this era right now that we've come out, we're coming out of a world of abundance, of being able to just be very comfortable and focusing our technology without really focusing on what is the business value around this? And I think the history that you're telling us is that if you go back to our roots, this all started because of business value. I think this is a very important message, and why I tell people always we need to understand our history otherwise we're doomed to repeat it, and then you're explaining very clearly that this is about understanding the customer, being able to go sell more. This is an important message.

Bill Inmon: And other business value as well. As important as the customer is, and believe me I'm a big fan of looking after the customer, there are other business activities. Such things as how many products do we have, how many sales did we make? If a business can't answer those questions, a business is in trouble.

Juan Sequeda: This is my big kind of soap box right now, everywhere I'm going off and talking about, " Show me the money, show me the money." Like, " You want to go do this new tech, you want to go do this?" Every single new kind of quote unquote, " Feature," which is a category that people are trying to go sell things, I'm like, " How is this going to provide value, what is the business value?" I mean, please share kind of, what is your message to everybody out there who's just so still kind of focused on technology?

Bill Inmon: Okay, I'm going to say some words that are going to make me a very unpopular person. People are going to tar and feather me, they're not going to like what I'm going to say, except it's the truth and it happened last week. Okay, you asked the question, I'm going to give you the answer, or an answer. Last week, Microsoft announced something called... I think it's called Chatbot, number one it is a cool technology, it is a wonderful toy, and in terms of elegance it's great, it's wonderful, I have nothing but good things to say for Chatbot. Except that it doesn't address business value, that Chatbot, and I'm not even sure I'm saying it right, but it made the headlines of the Wall Street Journal last week. Evaluated it in our world by investors at $ 29 billion, but we've seen this before, Chatbot is not new. Take a look at what IBM did on that Jeopardy show with their Big Blue adventure, what IBM did was associative recall. And they built a machine that beat Ken Jennings and Roger Craig. And by the way, anybody that can beat an associative recall, a machine to beat Jennings has got to be darn good. And in fact beyond darn good, very, very good, excellent. But all it is is associative recall, and that's not what businesses need. Businesses don't need to know about the islands in Indonesia, or the... They don't need to know about how coconut reacts to something else. I mean, that's external information. What businesses need to know is, what about my business, what about the emails I get, what about the call center conversations I get, what about my contracts? And those are the kinds of places where there is great business value, and Chatbot does not address that. So Chatbot is a wonderful, glorious toy, but it's a toy, it's elegant, it's sexy, it's all of the things we would like. Yes, well obviously investors like them, they think it's worth$ 29 billion. But it doesn't address business value.

Tim Gasper: I love this perspective, this is the honest, no- BS show about data, and so we try to really unpack it. And I think that we love to get excited about these things that can beat Jennings, right? I was playing with GPT3 last week, and holy cow that's cool right?

Bill Inmon: It's cool.

Tim Gasper: Or generative art, right? Like, " Wow, check it out," right? But then it's like, " Wow, that's technology that's been trained on kind of what's been done in the past. But now how do we turn that into something valuable?" And there's certainly valuable technologies, valuable companies, and interesting use cases around that. But it's easy to get excited about technology that is a solution in search of a problem instead of a problem, and figuring out the right way to solve the problem, right?

Bill Inmon: You got that right. Chatbot, or whatever it's called, is a solution looking to solve a problem. But they're not playing in the right ball park, they're playing... Take a look at what happened to IBM Blue and Watson, I don't know if you saw some of the projections IBM was making for Watson. But if I'm not mistaken, in terms of financial, business stability, Watson achieved approximately 1% of what IBM projected, because... And whereas Watson today, it got trash canned last year. I don't know if you followed that. IBM divested themselves of Watson, and you used to look at the Masters Golf Tournament, and the Masters Golf Tournament, IBM would announce and show all these wonderful things Watson can do. But there was no business value there, and the people at IBM forgot to ask the most basic question, something that every NBA student should learn on day one. And that is, what is the business value, and how do we get to it? The people at IBM failed to ask that, the people at Microsoft failed to ask that.

Tim Gasper: Very wise words, and I think that we can fall into the same traps easily around all of this, and-

Bill Inmon: And investors. I mean, I tell you something, I don't... Believe me, if you listen to Bill Inmon for investment advice you're really dumb, you really are. But I wouldn't invest a penny in... It's cool technology, but it's a toy. I don't know, Mattel and Hasbro make toys. I would invest in them, because they know their toy business.

Tim Gasper: At least they know it's a toy.

Juan Sequeda: This is the essence of honest and no BS, I love this, I love this a lot. I mean, we've talked about this before, you said again or repeated, if you can't produce business value why are we doing this? And I think this is the question that everybody needs to be asking all the time, what are you doing, is it producing business value? And heck, if you just want to play around with a toy that's fine, but acknowledge that you're playing around with a toy and you're not producing anything.

Bill Inmon: And every day you should walk in, and the first question you ask every day is, " How is what I'm doing going to produce business value?" And if you're not doing that you're on the wrong track.

Tim Gasper: Amen.

Juan Sequeda: Amen to that. " Show me the money," what I say. " Show me the money, where is it?" Okay, we're running close on time, let's keep going for a while here because there's so much stuff. One thing that I want to go back to history here, is understanding the whole, we always... Inmon versus Kimball, when it comes to data modeling I think this is... Data modeling's another thing that I feel that has come and gone, and then kind of come back and stuff, and people are not reading their history, understanding this. Can you, in your words, explain the Inmon versus Kimball?

Bill Inmon: First off, on a personal basis I've known Ralph Kimball for a long time, I consider him to be a friend, and I've never had one bad word with Ralph Kimball, I never intend to have one bad word with Ralph Kimball. I read these things in trade journals and other places, and I personally think it's funny that people think that Kimball and I are at each other's throats, we're not. Kimball produced an architecture that was good for answering immediate questions, but Kimball did not produce or recognize the need for integration of all of these applications in order for it to produce good information. And I recommend the Kimball approach all the time to people, is what you're looking for is something quick and dirty, put it out there, use the Kimball approach. If what you're looking for is the integrity of the data, of... The thing that Kimball's missing is the integrity of data, the thing that... Now, I'm the first person to admit, is it easy, is it fast, is it cheap to create integrity of data? No, it is not, and I don't believe I've ever said... If I ever have said that, my apologies, I was drunk at the time or something. But I've never in my life ever said building integrity into your data is cheap, easy and fast. And so when people say, " Kimball versus Inmon," I ask them, " What are you looking for? You want a quick report? We'll give you Kimball. You want data that you can believe, and you can answer the question, 'How many products do I have, what sales do I make, how many customers do I have?' That's the difference in the architecture." So Kimball is answering one question, I'm answering another question.

Juan Sequeda: Very well- said, thank you so much for this. And I think that's a nice snippet that we're going to share with people when I think of coming directly from you Bill, so thank you very much. So one final thing before we go to our lightning round, what's next for you? We hear it's about knowledge crafts.

Bill Inmon: Well, Juan, there's another world out there, and the other world in the corporation is the world of text. And text has been, for a variety of reasons, neglected, ignored, whatever. But there's a wealth of information in text, there's probably more information in text than there ever is in any structured system that's out there. And yet it isn't being used in the corporation. And so I actually... I haven't abandoned data warehouse, but for the past 20 years or so I've been working on the problem of what do you have to do to bring text in the corporation into a usable, analytical format? And believe me, we do not have time to go into the issues of what you have to go through in text, that is a very complex subject. But once people start, and they are starting, God love the people, they are starting to discover that yes indeed there is value in text, yes you can go into text, and start to find important things that are really important for your business. And so, now nobody... The Gardiner Group, nobody recognizes that. But I'm going to tell you, it's business value that's going to get them, because we're showing people how they can get business value out of text. And again, it's not the technician that has any input into this, it's the businessperson. We talk to the businessperson, not the technician.

Juan Sequeda: All right, we're very excited to go see what you're doing, I think we're very aligned. We've been sharing a lot of correspondence around text, and cataloging, and knowledge graphs, and building all this stuff together. I think that's a whole other episode we can go talk about, as you just said, so much to go into that. But with that, I think this is perfect timing, let's move on to our lightning round which is presented by data. world, the data catalog for your successful cloud migration. I'm going to kick it off, so first question. Today you mentioned that one of the golden moments that triggered the whole data warehouse was that large corporations were struggling to answer questions like, how many customers do we have? How many products do we have? How much sales did we make? Data warehouse was the answer to that challenge. Have we solved that problem?

Bill Inmon: Some yes, some no. The answer is 50% maybe, I don't know what percentage. Some percentage yes, some percentage no.

Juan Sequeda: Do you want to expand on that for a second, why yes and why no?

Bill Inmon: Because a lot of people still believe in the vendor, and I was in a conference the other day, and the vendor was saying, " Man, this integration stuff, this integrity stuff, that's hard to do, it takes a long time. Let's just go do something called ELT, and let's just throw our data together, and let's not bother to integrate it and make it usable." And then people still listen to their vendors, and part of the maturity of our profession is people weaning themselves from listening to the vendors, or at least recognizing that the vendor is there to sell them, not to solve the customer's problem.

Juan Sequeda: Great. So I had a quick followup on here, so ELT and the lake house, the data lake and all that stuff, this is the problem? Honest, no BS, Bill.

Bill Inmon: The data lake was the worst thing that somebody could have done to our profession. It was something that... It's what happens when you put amateurs in charge of data architecture, and I don't even know who I'm talking about. But I know somehow the data lake came about, and it was the stupidest idea that I've heard. And so I'm going to make the remaining part of my career helping clean up the mess that people are making with data lakes. Now-

Tim Gasper: I love that.

Bill Inmon: ...a quick word, there's a difference between a data lake and a data lake house, that the people that are building data lake houses are headed the right direction. The people that are building data lakes are setting our industry back I don't know how many years, a decade, two decades, but they're going the reverse direction. But data lakes are a stupid idea.

Tim Gasper: I love your honesty, Bill.

Juan Sequeda: I love it, I love this.

Tim Gasper: Well you know, the funny thing is, the data lake house has always seemed to me to be a bit of a revisionist approach to, " Well, if we take sort of a data warehouse and we stick it in the middle of a lake, maybe it makes the lake a little bit better."

Bill Inmon: Well, a quick story, I had a conversation with the CEO of Databricks, and he didn't charge me. But on a relationship basis, what data lake house needed was a conceptual understanding of what was going on. So I'd been doing my best in terms of books and other things to give a conceptual foundation for the data lake house. And Databricks has been wonderful to work with.

Tim Gasper: That's awesome, love it. They're a great partner for us as well, both Databricks and Snowflake. All right, I was going to ask you for your next lighting round question, have the big data and no sequel movements taken the progress of the data warehouse backwards? But I think we kind of answered that, so I'm actually going to replace that with a slightly different question here, which is, is there a key missing role right now in the organization that is sort of this data to business, or data to knowledge translator? Is that a missing role right now?

Bill Inmon: Oh, you bet it is. And once upon a time, and it didn't go very far. But once upon a time, corporations had an internal training function for technology, and it was for the technician and for the businessperson. And that idea was... I don't know who started that idea, that idea was wonderful, that was a really, really good idea. But today, when you go out into the world, I don't know, that function may exist somewhere. I haven't seen it in a long, long time, but absolutely, the people still need education. But they don't need education about how cool the product is, they need an education on how to solve their business problems, and how to make the connection between their business problems and technology. That's what is needed. But I don't see that happening any time soon, I mean, I don't know, I'd love to be surprised.

Juan Sequeda: I think this is what I call business literacy, and Bill, if we don't see this any time soon we are freaking screwed and wasting more of our time and money. Because we need this, because otherwise it's just doing more technology for the sake of technology. At some point, I mean, this is unsustainable, period.

Bill Inmon: What can I say? But like all evolutions, in every evolution there has always been a couple of branches of the tree that kind of fell off, and so evolutions are not clean and neat, they are messy, people die, blood is spilled on the floor. And our evolution of our technology is exactly the same, it's an evolution and it's messy.

Juan Sequeda: Bill, you are a very wise man, that was a very wise comment. Next question, is data modeling a lost art?

Bill Inmon: Data modeling is absolutely not a lost art, it better not be because... It better not be. But there are new renditions of data modeling, so in order to understand the structured data of the world we need data models for lots of reasons, I can go into it. However, there are new forms of data modeling. When it comes to text, the new form of data modeling is taxonomy creation and ontology creation. And ontologies and data marks are related to each other, but they're not the same thing. There are some substantial differences between a data model and an ontology, but that's what's happening now. And when we lose the ability to data model, we have lost the ability to read the Bible. And God, I don't want to be on this Earth when this Earth loses the ability to read and understand the Bible.

Juan Sequeda: Yep, you know what? I'm seeing this trend that experts, people who have been in the data warehouse world from the beginning, are just kind of changing their conversations in a way about the focus on the semantics, on the knowledge, on the meaning, and that's what we're seeing more of the conversation, about knowledge graphs and ontologies. I mean, this is the world I come from, I come from the semantic web world. And 10 years ago I was told... 15 years ago I would say the word ontologies all the time, and then 10 years ago I would have said, " Oh no, don't use the O word, the ontology word, because that scares people, and people will think oncology, or think about philosophy, bleh." And now it's coming back, and I think it's coming back because we're realizing that the missing ingredient here is knowledge, it's me understanding. And it's always been there, and I think it just hasn't taken its first- class citizen approach right? As you said, data marks and ontologies are related, they're not the same, I agree. But we're evolving, and I think it's one of those branches that will get stronger and stronger while some other ones will just fall.

Bill Inmon: And let me tell you my experience with ontologies, as I've told you I've spent the last 20 years of my life working on the issue of text, and text and language. And I'm going to tell you right now, you can't do text and language analysis without an ontology. So we had to become experts in understanding how to build, how to create, how to use, maintain ontologies. And I don't go into this with anybody, but we probably have more practical experience in it, because we know how to take an ontology, apply it to text, and come out with something that's useful and valuable. And the other day, just in fact two days ago, I was talking with some people, some wonderful people, I'm not going to name where. And they said, " Let me show you our ontology." And I mean, I don't mean to be uncharitable, I really am not an uncharitable person. But what they showed me for an ontology, I said, " Oh my God, this is not one ten thousandth of what an ontology is." So people think they can't work with and build... Listen, we build ontologies every day, and we know how to manipulate and use them. We know how to make them do little back flips, and so... But we had to learn that if you're going to be somebody that knows how to deal with text you've got to be an expert in ontologies, because that is the golden key to being able to expert in. People in the world are afraid of them, and there's nothing to be afraid of.

Juan Sequeda: I'm with you on ontology, semantics, knowledge graphs, it's my life, everything I have dedicated my career towards, so this is music to my ears. Tim, last question on you, we've got to keep going here, we're almost done.

Tim Gasper: Yeah, yeah, yeah. Last lightning round question, so you know, I actually started my career in sort of data and things like that, actually in unstructured data. I worked for a company called Highland Software, focused on document management right? Then you've got the knowledge management field, you've got a lot around text, there's a lot going on in the world of unstructured. And then you've got databases, and data warehouses, and data analysis systems, and things like that, right? There's these parallel streams going on, and you mentioned that you're really focused on text and on structured lately. Do you see that in the next 10 years the unstructured world and the structured world are going to finally do much more of a merger?

Bill Inmon: Oh, yes. And much to the chagrin of the vendors that have been fighting it all along, but... And I'll tell you why it's going to happen, it's not going to happen because of technology, it's going to happen because of business value. Because people are going to discover number one, you can go into text and start to do things with it. And once you do that, you can marry it up to your structured systems. And once you do that you can get analysis and understanding of your corporation that you could never, ever get before. That's why it's going to happen, but it's going to happen because of business value. It's not going to happen because the venture capitalists... Venture capitalists ignore what's going on, don't get me started on venture capitalists.

Juan Sequeda: All right, all right. This has been a phenomenal conversation, and let's go take it to our takeaways, T- T- T- Tim, take us away with your takeaways. Let's start.

Tim Gasper: All right, we'll do the best we can here to take it away. So we started off the conversation, Bill, with you kind of mentioning that our profession is immature, right? You look at the history of medicine, or there are fields that have been around for thousands of years, and IT's been around for what, 50, 60 years, right?

Bill Inmon: Yeah.

Tim Gasper: And some of the signs of the immaturity are things like education, how it has to happen through the vendors a lot. Another sign of immaturity is the fact that we have to get our Snowflake cert, and our Tableau cert, and things like that, versus being able to like in the field of medicine, be able to get your doctorate in medicine in a more general way. And computers started off being very general, but then they differentiated, they specialized. And so that's just kind of the maturing that's happening in that field right now, but it's so early, it's such early days, and it's evolving so fast. And you walked us through the history, the history of computing, where... And first of all you mentioned how important it is to value history. Juan, I know you're a big fan and proponent of history, especially in the computing field as well. Bill, you mentioned Gene Amdahl, so now I know I've got some research to do to learn a lot more about Gene Amdahl, because that's important. So in the history of computing, first computers built by the US Army. Then next use case, the mafia using it to calculate race track odds, right? In general it all started off with a big focus on numerical calculation. But then Watson proposed this idea of the world market for computational devices, and someone had this golden moment of, " Hey, this can really apply to business." So you moved to text, you moved to applications, we get the database management system, we get transaction processing. And now that's really the second golden moment, where computers really were making a business impact. They were the partner to the business in your words, and then you get the personal computer, internet, mobile computing, and so much more. So it's so important to know our history, and how that led to the data warehouse system, which Juan, over to you for your takeaways.

Juan Sequeda: Yeah. So I think it's very critical to understand the history of the data warehouse, I mean the data was locked for a specific purpose or usage, in these databases. And you Bill, you were the person who was trying to express that hey, data could be used for more than that, than it was locked for in the'70s. And you got a lot of hate mail for that, but hey, look who won here on this stuff. Transaction data supports the application, while corporate data is there to support the enterprise, to be able to answer those questions of how many customers do we have, how many products and so forth, right? So what does it take to answer these questions at an enterprise level? It's enterprise data, not just application data, not just data from one application. And what I really love here is that the data warehouses was loved by the marketing organizations started here in the US, right? PacTel Cellular you said was the first one, they wanted to gain more market share, understand their customers, keep their customers. And then their competitors find out about it and they're like, " Hey, we want that too." So thanks to the marketing folks is how data warehouses actually started, and then after that you get Walmart coming in, and then that's it, it's now mainstream. And basically, IBM SCP, you were no help at all for this. Thinking about kind of business value, we have to be very, very critical about what is cool versus what is providing business value. GPT Chat thing, this is very cool, it's very elegant, but is it addressing business value or not? Like, we've seen this before in so many different tools. We brought up the IBM Watson, the Jeopardy stuff, but hey, this is all associative recall, is what you were talking about. They don't really understand my business. So even the folks at IBM during that IBM Watson era, they forgot to ask the basic question, what is the business value? Every day you work at a company, ask yourself, you wake up, " How is what I'm doing providing business value?" Finally, we got into that whole Inmon Kimball debate, got it very clear, directly from you. Kimball, you get a quick, dirty approach to ask questions. But it's not so much about integration, quick reports. Inmon, it is focused on the integrity of the data, on the integration. You must be willing to do something less fast, less inexpensive. You get data you can believe, that you can trust, that's where it is. And then what's next for Bill Inmon? An area that we have completely neglected is text, and all the text, we're going to bring in text and make it in an analytic goal format, and using knowledge graphs for that. And just to summarize some things you said in the lightning round, the data lake is the worst thing, the stupidest idea, and immature folks put in charge, and it's going to be your goal to clean up that mess. The data lake house is in the right direction. We need more education in how to solve business problems. Taxonomies and ontologies, we need to start focusing on this, and we will see the merging of unstructured and structured data because it's going to provide more business value. Bill, how did we do? Summarize our ....

Bill Inmon: You were wonderful. I want to close with one idea, I don't like data lakes.

Juan Sequeda: Period, period. Bill Inmon, " I don't like data lakes," period.

Tim Gasper: Can we put that on a T- shirt, is that okay?

Bill Inmon: You can do whatever you want to.

Juan Sequeda: All right, we're going to put that on our swag store one day, " I don't like data lakes." All right Bill, throw it back to you very quickly to wrap up here. What's your advice about data, about life, who should we invite next, and what resources do you follow?

Bill Inmon: Well okay, I get asked a question by young college students all the time, " What should I do?" And what I tell them, I give them this piece of advice. I say, " Get as close to the decision- making of the corporation as you can," because when it comes time for layoffs who's the last person to get laid off in a corporation? And that's the person that is closest to the decision- making. If you are working in a clerical function, in a Rotarian function, we need people like that. But you are open, and opening yourself and your family to layoffs. So if I have one word of advice to give young, young people, is get as close to decision- making as you can.

Juan Sequeda: Bravo, bravo, bravo, yes. Who should we invite next?

Bill Inmon: Oh. Well, I think Brad Pitt would be appropriate.

Juan Sequeda: You know, we've had another guest before who said we should invite Matthew McConaughey, so we've got to start doing this.

Tim Gasper: Yeah, this is going to be a Hollywood episode at some point.

Juan Sequeda: Yeah, we'll have to do that.

Bill Inmon: Fine, okay, sounds good to me.

Juan Sequeda: What resources do you follow? Books, people, conferences, events, whatever.

Bill Inmon: Unfortunately, in my life I've always been... I've had to go trial and error, because the places I've gone, there haven't been books and conferences in things like that. So my great teacher in life is trial and error, and it's a great teacher. Let me tell you something, a long time ago my young daughter, when she was, I don't know, three to four, was playing in the kitchen, and my wife was standing next to me. And my daughter was playing with a box of matches, and my wife wanted to run and grab the matches away from her. And I said, " No, no, no. We're going to sit here and watch her, we don't want her burning the house down. But she's about to learn an important lesson." And so she opened up the box of matches, she lit up the match, she burned her finger, not bad. But she remembered the pain, and pain is the great teacher. And so I don't follow books, or conferences, or anything like that, because all of my... Not all, but most of my experience in life has been trial and error.

Tim Gasper: Get your hands dirty and see what works.

Bill Inmon: That's right.

Juan Sequeda: Bill, this has been a phenomenal conversation. Just very quickly, next week we have Jane Urban, who is a VP of Data at Takeda, a pharmaceutical, and we're going to talk about data, and business value, and how she's been building a team in the US, and now expanding that data team globally. I think it's going to be a phenomenal conversation. Bill, thank you, thank you, thank you so much for this. Thanks to data. world, who always lets us go do this every Wednesday here. Thank you so much Bill, we will see you here in Austen in two weeks. Looking forward to that.

Bill Inmon: Sounds good, Juan. Talk to you later.

Tim Gasper: Cheers Bill.

Juan Sequeda: Cheers.

Bill Inmon: Cheers.

Speaker 1: This is Catalog & Cocktails. A special thanks to data.world for supporting the show, Karli Burghoff for producing, John Loyans and Bryan Jacob for the show music, and thank you to the entire Catalog& Cocktails fanbase. Don't forget to subscribe, rate and review wherever you listen to your podcasts.


Those who don’t know their history are doomed to repeat it. If there is someone who can speak to data history, it’s Bill Inmon. How did data warehouses start? Why is the computing profession still immature?

Join Tim Gasper, Juan Sequeda and Bill Inmon, the father of the data warehouse and Founder of Forest Rim Technology, to learn about the past and present of data, and where things might be heading in the future. 

Today's Host

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Tim Gasper

|VP of Product, data.world
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Juan Sequeda

|Principal Scientist, data.world

Today's Guests

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Bill Inmon

|Founder, Chairman, CEO, Best-selling Author