Alexis
Hi, everyone. Welcome to another episode of Data Dave Dives Deeper, your favorite bonus podcast to talk Tech with Data Dave. I’m Alexis, your host. You know me from Talk Tech with Data Dave and Data Dave Dives Deeper. I’m here today, as always, with my dear friend Data Dave, and we have a very special guest today to talk to.
Hey, Dave, how are you today?
Data Dave
I’m very well, Alexis. How are you?
Alexis
I’m good. I am excited for our guest today. We were doing a little pre-show chat there, and I think this is going to be a good conversation.
Data Dave
Yes, I think it is. We have with us today is John Ladley, who’s an author, advocate, and mentor for all things data. So, very excited to hear that and hear John’s story on the podcast.
John Ladley
Delighted to be here.
Alexis
So, listeners, I have to tell you how we got John on the show.
So, I was looking at all of the speakers at DGIQ that Dave went to and presented at a few months ago, and I saw John’s name pop up. I hopped on LinkedIn, and I looked him up and his bio and his backstory were just like, so entertaining to read on LinkedIn. And so, I reached out to him and I was like, “Dude, I want you on my podcast.” And John and Dave met, they had a great conversation.
We are super happy to have you finally joining us. I’m really excited to hear your background and to hear your story because like I said, what I saw on LinkedIn was very entertaining. And so, I think this will be good.
John Ladley
Good. Well, I shall follow your lead. I’m very happy to be here. Very flattered I was invited.
Alexis
We like to start the pods with a very simple question, which is: how did you get into data?
John Ladley
Let’s start with how I wasn’t in data and we’ll make this brief. I think DATAVERSITY did a similar question with me and three hours later, Shannon had to beg me to stop.
I started as a developer. I mean, I didn’t even start in it, for one thing. My first job, I was a disc jockey, and then I was a stockbroker. Someone said, “Would you like the job as a programmer?”
And I said, “A programmer? How plebian is that?”
And then my… it was a former girlfriend in college, and she said, “Yeah, but I’m making… $12,000 a year.”
And I went, “I’ll start tomorrow. Okay.” It’s 1979, I’m a stockbroker, I’m getting 7,000 drawn against commission, you know, and I’m eating Birdseye Pot Pies every night of the week or something like that. So, I get into it that way.
So, years later. But I’m a coder, assembler and cobol. I am a bottom level sitting in the massive room of cubicles for many years. And nothing ever seemed to work. Nothing ever seemed to work. I end up teaching classes at a university in the St. Louis area, which is where I live. I end up being at a defense contractor who lost a big contract because they couldn’t do software, right. Not data, software. They didn’t follow standards and methods. And so I got a job with them to get them into shape with standards and methods for coding and development work.
But their product, their product wasn’t software. Their product was data. They collected data, they munched it into reports, they made it accessible to people and then they sold the access to this data. It was like they were basically a decision support, which is an old word.
Dave has heard that before that you haven’t heard. Haven’t heard that since Jesus was a corporal. Right, Dave? Decision support system.
And we sold access to their own data, which was perfectly fine because that’s our tax dollars at work. Anyway, I realized that the data was the product. And all of a sudden I was standing in a doorway and that’s literally… I was in the right doorway at the wrong time. And someone said, we need someone to really clean our act up. Even though we’ve got our coding and stuff better, it’s still not working. And I said, “It’s not code anymore. We sell data now.” In the context of the 21st century, this is not an unusual conversation. Someone gathering data and packaging it.
This was 1985 is when we had this conversation.
Data Dave
I graduated high school in 1985.
John Ladley
You didn’t have to say that, Dave.
Alexis
I can beat you, Dave. Because I wasn’t alive.
John Ladley
You were. There was. Someone was a glean in daddy’s eye, as they say. Right? Okay.
So anyway, and years go on and I’m doing this stuff and I’m doing stuff downstream of this. I’m going to make this as short as I can. I’m doing professional things in a Big Five consulting firm and things like that. Downstream of this, no label put on it. Nothing.
I did a data warehouse. I hadn’t heard of a data warehouse. We did data quality projects. No one has heard of a data quality as a sub-discipline. And I just was very fortunate. I’m not a genius. I just put my head down, and I could make more money with this stuff than I could with the coding. Stuff.
But the key here is, from day one, I had customers for my product and my product had to be managed well and of good quality or they went to some other contractor to get the work. What I learned to live and breathe is what most organizations now try to attain in the year 2024. They still can’t do it.
And I know for sure it ain’t that hard.
All right, it ain’t that hard if you put your mind to it. That’s the short version of how I got here into data. And of course, you do this enough and you have successes and then I’m a little bit gregarious, as you might know, and then you go, I really wish I was still a disc jockey, you know, and stuff. So, you start to do things to have fun and speak and write and, and start to enjoy your work. Start, you say, “Look, I’m not going to die and say, I was miserable the whole time I worked. I’m going to be happy.” So I approached this and now because I’ve had such fortune, the mentoring and the advocating is what I do. I don’t do much hands on deliverable based consulting anymore. I am semi-retired, and I will talk to CEOs. CxOs are my main customers now. And I get to talk candidly, I get to say, you know, remember the old doctor joke, “’It hurts when I go like that’ and doctor says, ‘don’t go like that’.”
Data Dave
Yep.
John Ladley
I get paid money to say that joke basically is my, is my living right now. So, that’s the long and the short.
Data Dave
Excellent.
Alexis
Love that you started as a disc jockey and you’ve turned into a podcaster.
Yeah, the whole route there.
John Ladley
My own podcast started a couple of weeks ago. It’s called Rock Bottom Data Feed. I mean, tongue in cheek. It’s a tongue-in-cheek approach.
But I will say, like a lot of podcasts now, which we need, by the way, your podcast and mine and others is we’re done taking prisoners and being politically correct with folks. Okay? Vendors. A lot of your stuff is sucks, Okay?
A lot of your stuff, you’re well-intentioned. At the end of the day, you have got to make money. Your founders have a great idea. You go out, la, la la, here’s our product. Everyone goes, yay. And then you say, this is the best thing since sliced cheese. And you do it, but you don’t teach anyone that they’re going to cut their fingers off with the cheese slicer. Okay?
Data Dave
Yep.
John Ladley
We got to stop accepting that. We got to stop accepting that this is special. Governance is not special. My book, Data Governance, you know, but my book, that’s another. I have both plugs in in the first five minutes.
Data Dave
That’s very good and so natural.
John Ladley
That’s all right. Anyway, they were. Yeah, all the plugs are over anyway.
Organizations have governance. The board of directors, it’s in their job description, governance. CEOs number one job is governance. It’s oversight. It’s not fancy. Our profession is just making this so complicated and so hard. And really, folks, it shouldn’t be this hard. Well, what’s making it hard is you’ve got leadership over here in a zone of incompetence. I don’t mean it in a bad way. You’re either competent on something or the opposite of competent is incompetent. That’s not a pejorative.
Data Dave
Right.
John Ladley
It’s like the opposite of literate is illiterate. Right. All right.
Alexis
We did that one, too. Yep.
John Ladley
Oh, okay. You guys did that. Great. That’s a solid thing because I’ve had executives say, “Are you calling me illiterate? Remember who’s paying your bill.”
And I was like, “You know, I don’t need your money. You’re illiterate. All right. Can you read Russian, sir? Well, no. Then you’re illiterate in Russian. Are you insulted? No, you’re illiterate in data. Same insult or lack of insult.” We’ve got this huge gap between what people do over here and then over here. Technology people are not immune. The worst damn communicators around us are our own peers in the data industry.
Put them up in front of a bunch of executives and say, “Here’s your chance. You’ve been begging for this chance. Business alignment. Get an audience. You’re going to get by. You’re going to get it.” And they go, “We got to do a star schema.”
Totally blow it. Okay?
So, we also have a lot of incompetence, and I mean that in a kind way,on the other side, too, this is the Leaking Lena.
There’s an old pop culture reference for 1960s. If you guys do a trivia contest, what animated show did Leaking Lena appear on? All right. And if someone gets them right, send them something nice. Put that in the comments.
Alexis
Somebody out there, comment, yeah, answer that question. First person answer that question will send you a Talk Tech with Data Dave T-shirt.
John Ladley
There you go. There you go.
Alexis
I’m on board for that.
John Ladley
All right, click and subscribe, too, because you have to say that, don’t you?
Anyway, so that’s where we are.
Lots of other professions go that way. I’m sure double-entry bookkeeping went that way one time. I’m sure some dudes stood on the pyramids saying, “Debits, credits. What the hell is this stuff? I don’t know. I just got to build a pyramid. Just help me build the damn pyramid.” I don’t mind any of this fancy stuff, but no, you know, you need the debits and credits to know that the pharaoh’s not spending too much money on the pyramid or something like that. So, governance has been around forever because you need oversight. If you don’t have oversight, people do dumb stuff. Every so often, a certain percentage of population does stuff because they’re a bad actor. Okay. And you got to catch them, too. Not new.
Data Dave
So you keep using the word governance, you’re not using the phrase data governance.
John Ladley
Correct, correct. It is an adjective.
Data Dave
Exactly. So, I’m picking up on that. I’m gonna drill a little bit. You’re basically saying that governance is general and the fact that it’s data is just a part of governance.
John Ladley
Yes, absolutely. If you take the other mindset, you get what we have, which is everyone going, this is special. This is big. And I had someone say, I was in a social situation recently, and someone introduced her soon to graduate from computer science class, offspring to me. And you know, “Young Norman here is going to get a job soon. Hey, should he get a career in data governance John”? And I was like, “Well, how bored do you want to be? Do you want to be a nighttime hotel auditor? Because it’s about as exciting as that. Yeah, okay.Yeah. Because at the end of the day, what you should do is, did you do this right? And you add some stuff up or compare, fill out a checklist or something, and they go, yeah. And that means data governance has been implemented. Right.”
And there’s no extra money, there’s no cost, there’s no increase in overhead. It’s the first chapter of my book. First chapter, it says, no increase in overhead due to data governance. If you have any increase, you’ve done it wrong. Right. Yeah.
Data Dave
Because data is only evidence of behavior. So if you.
John Ladley
Yeah, yeah.
Data Dave
It’s all about governing the behavior.
John Ladley
What’s your definition of data?
Data Dave
My definition of data is very simple. My definition, data is evidence of history.
John Ladley
That’s really close to mine. Mine is now the 24 by 7 recording of human existence. Yeah.
Data Dave
I simply say it’s evidence of events.
John Ladley
Yeah. Now, let’s extend that. That makes that, you know what the word anthropology means?
Data Dave
The study of people. The study of people.
John Ladley
How people be people. Now, if we have the recording of events, your definition, or the 24 x 7 record of existence, by definition, that means data governance or oversight of this thing is an anthropologically oriented discipline.
Data Dave
Yes. A while ago, we did one on what is data? I have a nuance for that that I’ve been thinking about. Right. So data is the evidence of history. We had a question. Is there such a thing as good data, and is it too much to ask? My comment is everybody says we got bad data. We don’t have bad data. We have very good data about bad behavior.
Alexis
I think you actually said that in that episode, Dave. It was maybe like the third or fourth episode. It was, can data ever be perfect? And you were like, no, like, the data is good.
It’s what we’re doing that’s wrong and getting into that mindset is very interesting.
John Ladley
I gotta. The philosopher in me is looking around the room.
Alexis
I wanna double down. Why don’t we dive deeper on this?
John Ladley
Oh, that’s another plug. That’s a plug. Four plugs, 10 minutes in. All right. I’d say when you say there’s no such. There’s bad behavior.
If I’m documenting an event of somebody, and I pick up 42 things and move them over here, and that’s what the boss said. But the boss enters. I only did 40.
All right? So, the boss says, that’s the bad behavior. The boss put in the 40. Yes, but what if the boss put in 24? Transposed? Because, you know, whatever that is, when you say bad behavior, that might. Is it unintended behavior? Because bad has a value that has a connotation.
Data Dave
But I’m using bad very simply, as sort of. I’m not trying to drill into it or get too specific, but it’s the behavior that you’re tracking. You’ve still got record that something was moved. You’ve still got the event recorded. Yes. The data could be better. And for the purpose of the recording of the activity, the data could be good enough.
Right?
John Ladley
Yeah. Well, that’s the other thing. Data is… And this is the part about data that is different, that is special, is that data is unlike anything else in human endeavors, is much more contextual.
You know, if you look at engineering or finance, you know, I spent $42. On what? On something on Amazon. Okay, that’s pretty cut and dry. I look at 42 and I go, but I shouldn’t have spent 42. I should have spent 40 or whatever. There’s something contextual. Engineering doesn’t have that finance doesn’t have that healthcare doesn’t happen. The only human discipline that has that contextuality is art.
Again, art is very personal. It’s very human. We are more in a behavioral, human, anthropological area, I submit, in the 21st century. Data in the 21st century is not the data we had in 1970 or 1980. That was rows and columns and transactions. That was pure events, to your point. Pure events. Right.
Data Dave
That was pure events and pure capture. Now we’re into a much more nuanced structure, with the record of full behavior. As you look at the whole set of data, it’s a full record of behavior from which context can be derived.
John Ladley
Context needs to be known. Yes. To manage it.
So now if you look at context, now this oversight area, we won’t use the word governance, we’ll just call it oversight. This oversight of this resource or asset, whatever you want to call it is now has extra stuff in it. And now when we get into context, we get into use. We get into whether it’s bad or just inadequate or whatever. We are in realms of judgments and we’re in a realm of ethics.
Dara O’Brien, Catherine O’Keefe wrote a wonderful book on data ethics. They’ve already slammed into a second edition in like four years because everything is moving so fast in that. But we’re in this realm of whole different stuff again, iron and steel, capitalist running the place, row and column. DBAs and Ex-DBAs having to make this, make it real. We’re not prepared for this. We’ve got enormous, again, non-judgmental. We have enormous gaps in the capabilities of people to meet this challenge. And that’s where most of my mentoring and stuff goes is you’re not being fair to the people you’ve asked to do this. You haven’t given them the tools. We don’t even know what the tools are.
Data Dave
We don’t know what the tools are because as you said, this is an anthropological and a behavioral based structure where data is only a tool in and itself to monitor and track behaviors that we want to perform.
John Ladley
Yeah.
Data Dave
So by putting it in the hands of a DBAS, the DBA doesn’t know the behavior of the business, doesn’t know the behavior of the environment. They know their own behavior. But you’re putting it in the hands of somebody that really shouldn’t have that much power as well.
John Ladley
We’re getting better. I mean, we are getting better. When I talk to my peers, we’ve got a profession here that’s been data management. Let’s step outside of governance. But just treating data as another subject and not just the detritus of a transaction.
Data Dave
Right, right.
John Ladley
Or data was always to me, in my first book, I said historically, data was a lubricant of a business process.
Data Dave
All right?
John Ladley
If I have the data, I can do this faster.
Data Dave
I like that.
John Ladley
Okay, now data has gone from being the oil, the lubricant, to the gas.
Data Dave
It’s now the fuel. Right.
John Ladley
It’s gone from lubricant to the fuel and it’s multi purpose. I actually compare it to a car. The real automobile you might drive has an internal combustion engine, and it uses the oil for lubrication and the fuel is the gasoline.
My hobby is aviation. I have an 83-year-old airplane that I restored. All right.
Data Dave
Oh, very nice.
John Ladley
World War II training trainer, biplane. The picture on the back of my book is me sitting in that airplane and I do all kinds of stuff and it’s, it’s fun and it’s a huge passion, but it has oil and gas in it. The oil in my airplane is also used to cool the engine, and I don’t have a radiator.
Okay, your car has four quarts of oil. My airplane has four and a half gallons of oil. The use of it and my understanding of oil and everything is entirely different. And my airplane has wings and a cockpit and wheels and a tail and a radio and like all the other airplanes do. But if you ignore the value of the, of the. It’s not a lubricant. It’s got a bigger role. It’s got a much bigger role in my airplane. And it’s a whole different mindset. When you fly something like this, it’s called a radial engine, you have a different, you have a different brain, brain thing.
And, and we’re in that realm with data, but for some reason it’s like we’re stuck in this unit record thing with data, this lubricant thing with data. And I started the conversation, we’re getting better, we’re getting better. When I started in this and someone said the writings in the late 90s was Gwen Thomas, I think was the first person to really write about governance instead of enforcing standards is what we called it before. And so, and she was writing about it and I went, oh, governance, that’s the perfect word because my degree is in accounting.
I was a CPA before I was a disc jockey. I got my CPA and I said, “I ain’t going to do that.” I became a disc jockey. Well, I made dad happy, you know. You know, it’s like when I grew up and went to school, women got an elementary ed degree in case they didn’t get a husband. Yes, that’s politically incorrect, but that’s the way it was. All right, you can’t argue history, but man had to be an engineer or an accountant because. So you could take care of the home fires and stuff like that.
Alexis
Bring home the bacon, Right?
Data Dave
Yeah.
John Ladley
You know
Data Dave
I was an engineer so I fall in that.
John Ladley
There you go. So, I was an accountant, trained as an accountant. Think like an accountant. Still a lot to this day. But we’ve changed from that type of orientation to where we are now with data. Now, accounting has matured. I mean, at one time, like I said, some Egyptian engineer was like, “I don’t need debits and credits.”
Data Dave
You’re right. Accounting has changed because accounting has moved in priority from bookkeeping as just the tracking of accounts up to predictive forecasting and often driving the business. Right.
John Ladley
It’s that exactly, movement.
Data Dave
It’s moved from Dickensian bookkeeping.
John Ladley
Yeah.
Data Dave
Up to where we are now, which is often the leading of where are we going to go? How are we going to get there?
John Ladley
A CFO job. CFO job is a whole different job than the old corporate controller. Right. I mean, it’s a whole different thing. But along the way, to make it mundane, we came up with some principles. GAAP. Okay. Generally Accepted Accounting Principles. We don’t have generally accepted information principles. Now, I trademarked that at one time. I made a list of them. Doug Laney made a list of them in his Infonomic books. But they haven’t been adopted. No, but there should be such a thing.
Standard good data governance frameworks are now developing. Okay. Where you have good accounting frameworks and you have good practices, There are now good guidelines to build frameworks around accounting. And then we’re also beginning to define the difference between a framework and an operating model.
Finally, one thing I’ve succeeded in the last 10 years is quit saying data governance organization. There is no such thing. It’s a data governance organization that immediately triggers management into cost center… budget… I need to hire people… I don’t want to talk to you…. All right. So, you know, so we are making progress. I mean, Gwen Thomas started with a very interesting framework back in the early twos. It has evolved and I’m going to guess it’ll evolve again because Gwen’s back into a guru consulting space. Myself, I have a couple of things like that. I know Bob Signer has a lot of stuff.
Data Dave
We have one too.
John Ladley
Yeah, and. Okay, you guys got one too. So, we are maturing. We’re starting to codify some things and.
Data Dave
They’re getting remarkably similar. If you read a few of them and look around, they are converging.
John Ladley
Well, they have to be. They have to be. Because, I mean, how many double-entry bookkeeping systems are you going to come up with? If you’re engineering, suppose you’re in engineering. All right. If you’re an electronic engineer, you know that the diodes have certain color schemes on them and resistors have. And those color schemes mean certain things. And you’re not going to say, “Well, I don’t like that drab olive is a 5 microfarad resistor. I would prefer it to be a bright pink color.” Nobody’s going to do that. Once the standard’s in. The standards in, nobody cares, you know? You know, so we’re sneaking up on it.
Alexis
I have really enjoyed listening to the two of you talk about these topics. This is a lot of things that we talk about on a regular basis. Dave and I do. But I love hearing another perspective on a lot of these things. So I appreciate your time, John.
John Ladley
Yes, my pleasure. Very much. My pleasure. Thank you very much.
Data Dave
Excellent.
