Data Governance: Any “Dummy” Can Do It!

with Dr. Jonathan Reichental, Author and Founder, Human Future

Dr. Jonathan Reichental, Author and Founder, Human Future

Dr. Jonathan Reichental

Author and Founder, Human Future

Jonathan Reichental, PhD, the author of Data Governance for Dummies, is the founder of Human Future, a global business and technology advisory, investment, and education firm. He’s been a senior software engineering manager, a director of technology innovation, and has served as chief information officer at both O’Reilly Media and the City of Palo Alto, California. He has also written three books on the future of cities.

Satyen Sangani, Co-founder & CEO of Alation

Satyen Sangani

Co-founder & CEO of Alation

As the Co-founder and CEO of Alation, Satyen lives his passion of empowering a curious and rational world by fundamentally improving the way data consumers, creators, and stewards find, understand, and trust data. Industry insiders call him a visionary entrepreneur. Those who meet him call him warm and down-to-earth. His kids call him “Dad.”

Producer: (00:03)
Hello and welcome to Data Radicals. In today's episode, Satyen sits down with fellow data radical Dr. Jonathan Reichental. Jonathan has penned several books in the For Dummies series that make data transformation actionable for everyone. In this episode, he gives a step-by-step guide to implementing data governance, explains how to avoid common governance failures, and shares insights on the future of smart cities.

Producer: (00:32)
This podcast is brought to you by Alation. The act of finding great data shouldn't be as primitive as hunting and gathering. Alation Data Catalog enables people to find, understand, trust, and use data with confidence. Active data governance puts people first, so they have access to the data they need with in-workflow guidance on how to use it. Learn more about Alation at

Satyen Sangani: (01:02)
Our guest today is Dr. Jonathan Reichental. Dr. Reichental runs Human Future, a technology and education advisory firm. He's a professor and instructor at several universities, including the University of San Francisco, Pepperdine University, and Menlo College. Dr. Reichental served as chief information officer at both O'Reilly Media and the City of Palo Alto. He is the author of six books, including Smart Cities for Dummies and most recently Data Governance for Dummies. Dr. Reichental, welcome to Data Radicals.

Jonathan Reichental: (01:32)
Oh, thank you very much, Satyen.


Writing a Dummies book

Satyen Sangani: (01:34)
So let's start with the most relevant topic to this audience, which is, Data Governance for Dummies. What motivated you to write this book and why in the For Dummies series?

Jonathan Reichental: (01:47)
[chuckle] Yeah, that's a great question. Back about 4 or 5 years ago, I had the chance to create an online video series on data governance. I did it for LinkedIn Learning, and it became actually very successful. Having been a technology leader for almost 30 years, I had a few things I could say about the topic, and of course, as a technology leader or as a CIO, you're in that role, you're managing and governing the data as part of your role. And so I was able to bring those experiences to the table, as well as some of the formal frameworks and tools and things into that course.

And later, I had an opportunity to get a publishing deal with Wiley, the major publisher and did Smart Cities for Dummies. It was a successful book, and they were doing their own research on who would be a good candidate to write a book about data governance. And one day I got a phone call about a year and a half ago from my editor, and he said, "We see that you've had a successful course. You know something about this topic. Would you be interested?"

Jonathan Reichental: (02:52)
And I have to say, writing a Dummies book is actually quite hard because it requires a certain level of language, plus it's very structured. And it was hard for me to write the first one, so I had to think about it deeply.

They presented to me where the market was going. They said, "It's clear that data governance is quickly elevating in terms of priority for leaders in all types of organizations, and we see a strong demand for content and education around the space. If you write a book on this, it's gonna be, hopefully, if you write it well, we'll have good high demand." So that was convincing to me. I always wanna be useful and to educate and reach a large audience, so I said, "Okay, I'm in." I just wrote it knowing that this was a very well-respected brand, and we could actually use the structure and style of it to make it easier for people to understand this important topic.

Satyen Sangani: (03:47)
The branding is incredible because it takes topics that would be otherwise really hard to access and are difficult and really demystifies them, and also just starts from a position of putting the reader into a place where they're automatically humble. And so it's super disarming and very cool. So what is it about the structure of a For Dummies book that makes it both so hard to write but also so popular and accessible?

Jonathan Reichental: (04:14)
This is the most popular reference series of books ever created, so it's really quite a big brand. Well, if you pick up three Dummies books and flick through them, you'll notice that they're very similarly organized. They're in parts, and the parts have chapters and chapters have certain layouts. So you have the intro, and then you have the sections. And all of that creates a lot of rigor for an author, that may be if you just wrote the book yourself for a different brand or just wrote a book you wanted to write, you would make all those choices yourself. But no, you have to sort of conform to their template, if you like. The other thing is, when you work with your editor, and they're terrific editors, they push you to be very clear and action-oriented. You can't do fluff. They're gonna push back. They're gonna delete sections. So it's actually good discipline for an author. It's not for everybody, of course. Some like to be a lot more elaborate in how they describe things. They want to incorporate more of their own personal style.

Jonathan Reichental: (05:19)
I'll give you one quick story, which kind of both proves and also disproves something I'm gonna say, which is when I was writing The Future of Cities, one of the things I put in the table of contents when I was — that's the first thing you do when you create a book — I had a lot of history. Like the history of cities, the genesis of cities, and I sent it into my editor and they turned around and said, "Dummies books don't do history. We do right now. What does the person need to know right now?"

And so that's part of their thing. And in support of Dummies, I could say I like that because there's no fluff, the person who reads the book gets what they need right now. But I pushed back, and I said, "I think people need to know the history of cities in order to understand cities today and where cities are going." And they actually allowed me to do that. They accommodated my perspective, which was very unusual for a Dummies book to put a historical context into it.

Satyen Sangani: (06:14)
Yeah. And I would imagine if you do have the context, it makes the present a little bit easier to explain, so I think obviously, it's great to know that there's some agency with the author. What part of Data Governance for Dummies was hard to write? Because most of the books that I've read on data governance, honestly, speak super conceptually about the topic, and I've certainly read books where I've left more confused about the topic than actually educated. What did you find was hard about data governance to explain?

Jonathan Reichental: (06:47)
Well, I have had the same experience as you. And if someone did a search online for a book on data governance, they're gonna find results. They're gonna see that this topic has been written about. And in doing my own research, I bought several of them, but I recognized, much like you, a couple of things. Number 1 is some of the books were really complicated. They assumed that you had a lot of prerequisite knowledge on just computer science overall and data science. I didn't like that because that wasn't gonna work. Then I read some books which were so fluffy, they didn't give you any advice, and you ended with saying, "What do I do now?"

So I had two missions. I wanted to, in a book, write something that anyone could approach, to use your words from earlier, a book that was more accessible, and I wanted it to be action-oriented. So when you actually buy the book, tomorrow you could start building a program.

Jonathan Reichental: (07:39)
I think the next point is, it is a tough topic, and it is a topic that if you write in a certain way, it can be boring. And I say that with great love for this field and great love for data and computer science in general and the value it has in society. So I actually wanted to write a book that was engaging, that took you through a journey from creating a vision for your organization, right through to measuring that and operationalizing an effective program. I wanted to write about the value of data governance to your business and your organization. I wanted to be able to convince the reader, so they don't have to go out and Google for hours and read all the academic journals and all the blogs and stuff, that they could read in just a few pages, "Why is data so important and why do you need to prioritize it and ensure it's better quality and you're making sure that it's secured and all the other stuff that goes with data governance?"

Satyen Sangani: (08:35)
Yeah, and I just wanna make that case here because I think people, obviously, listening to the podcast, believe it, but a lot of the value you get from it is speculative and in some cases unrealized. So how are they gonna convince people to invest in this thing called data?


How do you convince people to invest in data?

Jonathan Reichental: (08:51)
One data point that I thought was very valuable is, when leaders of organizations of all types were asked whether they want to prioritize being a data-driven organization, it's over 90%. And basically every leader wants to ensure that they can make better decisions using good-quality data, because that means if you can do that, you can go to market faster. You can target your customers in a more efficient way.

It also means that if you're data-driven, you protect the data that you have a responsibility to. You don't get into trouble. Data is important because you're often managing data on behalf of your customers and your stakeholders, and if that data gets breached and we hear all too often about that, there are fines, right? There's monetary fines. There is bad publicity, right? It damages your brand. I mean, the consequences of not managing data well are exceptionally evident, right?

Jonathan Reichental: (09:55)
On the one hand, managing means you get better results, so we have real support that organizations that do data governance well get better results in the marketplace. They're more profitable. They grow faster. The data is really clear on that. Equally, organizations that are poor at data governance don't get that benefit, but they also have more breaches. They have more compliance failures.

So when you add it up from the offensive data strategy, which is to know your market and grow your business, and the defensive, which is to protect your data and make sure your operations are efficient, couple those with really efficient decision-making — timely, good-quality decision-making — those are some very strong compelling arguments. And leaders want to get there. They actually demand it. It's not me or the data governance person coming forward and saying, "You ought to do this." They're asking, "We wanna do it. We simply don't know how to do it, and unfortunately when we do, we're failing far too often."

Satyen Sangani: (10:53)
But it is one of those things that is perhaps important but not always urgent. What in your experience brings it to become something that's urgent for an organization? How do people make that case?

Jonathan Reichental: (11:08)
So part of answering that question is, what's holding leaders back? Why wouldn't they do it? If it's clear there are so many advantages that I've just described, why wouldn't they do it?

So part of it is they don't know what it is. Data governance sounds bureaucratic and cryptic, and they don't... "Actually, tell me what that is." So there's an education piece to it, so they don't know. They think it's expensive, and they're like, "Oh, my goodness, I have to invest more money in overhead." And number 3 is they think it's too much bureaucracy and too complicated.

So there are these reasons why leaders wanna be data-driven, but they don't pursue data governance, right? And so you have to convince them around those limitations or things they see as restrictions. You have to say and have the arguments in place that, "Actually, data governance can be sized relative to your business.

Jonathan Reichental: (11:57)
"If you're a small, successful business or you're a small business, you don't need the same level of rigor as a highly regulated Fortune 500 company." You can deploy and see benefits from data governance very quickly without massive investments, without having to buy very expensive suites of tools, right? The entry point is actually quite low, but as you mature and you see the value, you can obviously buy more tools and you can train more people and expand the purview of data governance across your organization. And one of the things I talk about in the book a lot is how you get started, and then don't start by trying to govern all your data sets on day 1. That's a recipe for failure. Pick the ones that would have big bang results quickly. Like maybe pick 1 or 2.

Jonathan Reichental: (12:43)
“If we as an organization knew a little bit more about our customers and that was data that could be kept current and secured in the right way, we could make better decisions and move more fast and more quickly in the market.” Go after things that are really important to you. So I think it’s making the strong case on why it's valuable but then also helping break down those which are often mental limitations of cost and bureaucracy and overhead.

Satyen Sangani: (13:11)
I wanna come back to the 10-step program that you lay out 'cause I think that's really important and relevant and, to your point, pragmatic. Before we do that, though, describe what is your definition for data governance and where did you get it from?


What is data governance and how does it relate to data management?

Jonathan Reichental: (13:27)
Data governance is about managing data well, and it's everything that helps in support of that to create better quality data that gives you standing results in your business.

One of the ways I think about this question is, if you asked what organizations or how many organizations manage data — do they have data management in place — I would say every organization. Today, there isn't a business that doesn't have tech at the center, and as a consequence they're managing data.

But then the next question is a simple question, and you get a completely different answer. Are they doing it well? Is it secure? Is it compliant? Is it actionable? Are you building your business on top of the rich insights you can get from the data that you have or can collect from the marketplace? And that answer is often, "No, not as much as we'd like to," or, "I don't know."

Jonathan Reichental: (14:17)
We've got a layer of processes and responsibilities that we can put in place — and tools — that can allow organizations to achieve those better results to manage data much better than they do today. And depending on your vision, depending on your goals for data for your business, that can be lightweight or it can be a significant investment. It all depends on what you establish as your vision for data governance.

Satyen Sangani: (14:44)
One of the things that — and this is not intended to be a sort of gotcha question, but I did wanna understand — in your assumptions in the early part of your book, you mentioned that data governance is not data management, but you define data governance as managing data. So how is data governance different from data management, and what does it mean to manage data?

Jonathan Reichental: (15:05)
The key part of data governance is about managing data well. The well is the key word there. It's like doing it better than you're doing it, and doing it much better and getting much better results. So data management, and this comes up a lot — people actually do confuse the two terms — or they know what data management is, but they have no clue what data governance is.

Data management is the action of working with data. When you manage data, where do you store it? Do you put it on a server? Where is the server? Do you move data? If you move it, what software do you use to move it? How do you process it? How do you secure it? What are the admin rights and things? It's really the action related to data. Governing is the rules, the policies, the approach you have to those actions. It's that layer above it. Who does that? Why do they do it? When do they have the rights to do it? So they are distinctly different.

Jonathan Reichental: (15:32)
Now, governance is one of those things that exists informally just as a nature of existing, but there's levels of it. There's the informal governance of, "Yes, we store data on a server and the IT manager has access to it." And you could say, "That's data governance, but is it correct, and is it the right approach? Is that the right person? Is it the right level of access?" And those things have to be defined, and there's rigor in defining that. And it just goes from there.


What’s the starting point for data governance?

Satyen Sangani: (16:29)
So how does this start? Where do people most often... Real-world example, if I were to start the smallest possible way, what would that look like?

Jonathan Reichental: (16:38)
For me, the starting point is, "Why are we doing this? What is the goal of data governance?" So you have to establish that and you need to establish that with a broad set of stakeholders. This is something that you need to bring in participation from across your organization, develop that vision.

Is your vision for data governance to be an organization that by doing data governance, you can grow by 10% over the next 2 years? Do you have some very specific goals like that, or is it over the last 5 years, annually, we get at least one major security breach? Data governance, we wanna reduce that either by half or eliminate it, right? So you have some overarching vision for data governance, and you get buy in. You've gotta work hard as an organization to ensure that there's some level of alignment and that people know why you're doing it and those results that you would like to see happen.

Jonathan Reichental: (17:28)
The next thing is you need a strategy. And one of the questions I always ask organizations is, "Do you have a current executable data strategy? Do you already recognize data as your most valuable asset, or is it driving your business or do you think of data as a byproduct of what you do as opposed to the asset that drives our business growth in the marketplace?"

And unfortunately, the reality is many organizations don't have any data strategy, which is all too common. Or number 2, they do have one, but it's not current and it's not being executed against. So you really need to have an active data strategy. In my book, I tell you step-by-step how to create a data strategy, which is supporting, first of all a much more enumerated way of achieving your vision, but then the steps and the projects and the efforts to get there.

Jonathan Reichental: (18:14)
Now, the question is, is data governance baked into that? Is that part of how you are executing upon your data strategy for your organization? The 3rd part is you've defined it, you've got a plan, not what are the roles and responsibilities? And who's gonna do what?

Now, I get asked the question often, "Who's responsible for data governance? Is it like a data governance manager? Is that it?" And the answer, sadly, [chuckle] I guess for folks, is that everybody is responsible for data in the 21st century. It's a key asset for your business, and everybody has a role. Everybody is managing data in some way whether it's putting an attachment on an email or accessing a data repository, maybe running a report, exporting data, sending that data to a client or something. You're all doing that, and if you ask that employee, "Do you know what your responsibilities are, relative to that data?" You might be surprised by the answer.

Jonathan Reichental: (19:04)
They might say, "I haven't thought about it. I don't know." Then you have people who are deep in this. And for succinctness, I'll just mention one, which is, this is also a question that is often asked and with a bad answer is, "Who comes to work every day and cares deeply about important data sets?" The answer often is nobody.

Jonathan Reichental: (19:25)
Organizations don't think about data ownership nearly as often as they should. We call that role... Sometimes the broad role is called a data steward, but it's also a data owner. And there can be different types of data owners, depending on the organization. Some very big complicated businesses have full-time data stewards for big sets of data sets. Others, it's in a small organization, it's just part of somebody's role.

And you don't need data stewards for every single data set, right? Only for stuff that really matters. So there's that. And then 4th point is metrics. Like, "Now you're actually doing stuff, and what are the results? Are you measuring the results of your data governance program?" And 2 things can happen. One is, yes, you have good metrics, and you share those metrics with stakeholders. You say, "Look at this. In the last year, we've been doing the following rigor, and we're getting better results."

Jonathan Reichental: (20:18)
But also, you can go back and say, "We put data governance in place, and it's having absolutely no effect," right? In which case you've gotta change the data governance program or something's broken, and metrics will tell you that.

Satyen Sangani: (20:30)
So vision, strategy, people and metrics. Those are the four steps that we've reviewed so far.

Jonathan Reichental: (20:38)
Those would be the high level. Yeah, yeah. Nicely summarized there.

Satyen Sangani: (20:41)
It sounds like... Frankly, if you take those elements — vision, strategy, people and metrics — it sounds like it's like any other cross-functional strategy that a business might run. We have within Alation strategic initiatives and literally the way we define them are vision, mission, strategy, initiatives and each of the initiatives have metrics, and then each of those metrics have actions or projects as you pointed out that we use in order to be able to move the metric. So it sounds very cross-functional. One of the things that I've found with data governance, before you set up all of this infrastructure, before you set up this framework, which I think it is, it sounds like a fairly useful operational framework or organizational framework, what I find is that people, when they say, "We need governance." We meet hundreds of people, thousands of people every year at Alation through our sales force. And often you hear these words, "We need governance."

Satyen Sangani: (21:38)
And then you say, "Okay, let's go into that conversation a little bit more deeply," and the person says, "What we really need to do is prevent people from accessing the wrong data sets." And so what they really mean is data access governance, and often if you talk to a database vendor, when they talk about governance what they mean is data access governance. And then sometimes you say, "What do you need governance for?" People then say, "Everybody's using the wrong data." We all have these definitions and none of the definitions comport, and really there’s a business glossary which is needed. And so there's all these kinds of artifacts of governance, but people seem to say the word “governance,” but often they mean this very specific thing. And so the irony of this is like the semantics are really muddled when one of the big things about data governance is supposed to work out your semantics. How does one resolve that, or at least what does one do?

Jonathan Reichental: (22:25)
Well, let me say a couple of points. Within the four steps, one thing that I wanna don't lose sight of is you gotta implement some stuff and maybe that's during the executing on the plan. So there will be tools. Like in the case of good data governance, you may build out a catalog, for example, the glossary. So I wanted to just highlight that. Doing these steps, we don't lose sight of the fact that there's a build element in there too. When some of these things are in place, they're operationalized. That's a key part here.

I think your question, though, fundamentally goes back to the beginning, which is what is the point? What's the vision? What are you trying to achieve? And if you discover, talking to a leader, that in fact they just wanna have better control over who accesses certain data sets, you'll optimize for that, but it does invite a bigger discussion about how you're approaching data.

Jonathan Reichental: (23:12)
And again, you could say that it allows for a bit of a gap analysis. What are you doing well to get good data results? What are you doing not so well? Which one of them is the driver for this conversation, but are there other aspects that if you go after this, you'll actually achieve some other results with just a little bit more effort?

So I don't mind the idea that early on you're going after some very laser-focused objectives. I do think in the long run, though, data governance is not about a narrow target. You will build a better business if you hire all the right people, if you build the right products, and deliver the right services, not by doing just one thing and doing it really well, it's a comprehensive approach to running a successful business. And I think data governance should be thought of in the short-term as targeting some very specific things, but long-term as a cultural shift in how you actually think about data and how you use data on the back end and in the front end of your business.


When is a data culture ready for governance?

Satyen Sangani: (24:11)
Part of your book is about knowing if your data culture is ready for data governance. I think this is actually an important idea because you could be very early in this continuum, where all you're trying to do is block access to a data set that contains social security numbers. And that could be like your big goal, and it might be premature to call that data governance.

When do you know that you're ready for this particular thing? Like how do I know that I want governance with vision and strategy and the like as opposed to just a couple of rules in place to go manage a database?

Jonathan Reichental: (24:42)
[chuckle] That's a good one. Yeah, there's always gonna be a number of different triggers for a question and actions. Often it will be that something's happening. There's a problem. A phone call will happen to a vendor when you're having a problem, like, "We're getting attacked. Help us. We fail in our compliance requirements every year. Help us with that." So sometimes you are responding to this problem.

But there's a bigger question that leaders are asking now — and I saw that in the research that I did during the development of the book — senior leaders of organizations have noted that, obviously, we're operating in a hyper-competitive environment. Every day is a hustle. There's somebody ready to steal your client or build a better product. Leaders know that. Leaders know that they're sitting on tons of data that they don't use, that they're not taking advantage of the incredible insights that sit in those massive data sets that we all either have access to on the outside or contain as our IP internally.

Jonathan Reichental: (25:44)
And they ask the question, "How can we be more data-driven? How can we make better data-driven decisions?" And those broader questions, I think, are answered with a comprehensive approach to data governance. So in a way, later on, I might think differently about your question, but right now I see the entry point is either a pain point or it's a bigger strategic effort.

I have a statistic here, which I think, again, is validated through research. One of the reasons that drove the book was the publisher in their research recognized that there was increasing interest in the topic. Why? What's going on? We're in this period of data explosion, the zettabyte era. Never has there been so much data of so much variety and velocity than ever before. And organizations are recognizing. They're also recognizing a more regulated world in which they operate, a world in which there are much more cyber security risks and one in which they want to be able to make timely decisions.

Jonathan Reichental: (26:39)
And so the data point that I thought was most interesting was, in the next 12-18 months, over 30% of organizations of all types will make large investments in data governance. So they're being driven by this, that the market in my view exists and it's been driven by those pain points or by a large strategic initiative.

Satyen Sangani: (27:01)
And so when you know that you're in this 30% group is when you've got enough social, political will within the organization in order to make it happen. There's a sort of ground swell as it were within the organization.

Jonathan Reichental: (27:15)


Why do so many data governance initiatives fail?

Satyen Sangani: (27:17)
You mentioned that... You cited another statistic in your book that 90% of organizations fail at their first attempt at data governance. That sounds horrible.

Jonathan Reichental: (27:26)
It does. [laughter]

Satyen Sangani: (27:28)
And what percent of these 30% are on their 1st attempt versus their 3rd?

Jonathan Reichental: (27:34)
That's a good... That 2nd question is, I don't know the answer.

Satyen Sangani: (27:37)
Fair enough, fair enough.

Jonathan Reichental: (27:38)
The 30% includes those that are making greater investments and those that are making investments for the 1st time of all organizations, so that's a sizable change in the market's demand for data governance. I was alarmed also like you with that 90% failure on the first attempt, and of course, if you dig into it a little bit, what is failure? Did the whole thing completely implode or did they not get... Did they only get 50% of what they were hoping for? What you find is it's almost case by case, but some of the themes are insufficient buy-in. The organization wasn’t all over it. Somebody was — the CIO or the chief information security officer, maybe the CEO, if you're lucky — but there wasn't buy-in from across the organization. That comes out in the data. So there's that. Number 2 is leadership. Something that I write about quite a lot in the book is you have to have a passionate leader or leaders who drive this.

Jonathan Reichental: (28:40)
During my career, much like yours I imagine, I've managed a lot of projects and technology projects, and unfortunately, the statistics on this are pretty bad. There's a high degree of project failure in every type of organization, and the question is why? Why do projects so often go over budget, they're late and they don't meet their needs? And the No. 1 reason is leadership, is a sponsor. And that means that that sponsor believed in the project 100% and remains engaged in the project right through the end through to delivery. When that happens, the likelihood of success is much, much higher. Now, data governance is a program, and it needs a passionate leader who's gonna run with it. And this is sort of an executive sponsor. It's probably somebody from the C-suite. They need to be involved throughout.

Jonathan Reichental: (29:27)
The 3rd one, I would just say is we see this not only in programs like data governance and projects too, is poorly defined outcomes. Was it really clear what you were gonna do, and how you would measure it? And if people have different ideas, this comes with the misalignment problem, and everybody did their best, they weren't all on the same page, the metrics might not be so great at the end. And then the outcome is, "We didn't achieve what we wanted to. This has been a failure."

Satyen Sangani: (29:52)
It does map back to this idea that it's a strategic initiative, and with all of these things like any action, entrepreneurial action, business initiatives within a company, it ultimately just comes down to like, "Do you know where you're going? Do you have the right people to get there? And do you define scope well enough to know how you're doing along the way — and metrics, of course."

One thing that... It's come up with more than one CEO, but one chief data officer said to me, this is somebody who led data for a large contract research organization, and she said to me, "We don't actually call this data governance anymore. We call it data enablement," which I think in your book you refer to as “data governance has a PR problem.” Talk a little bit about that. Do you think there's any merit in marketing it as something else or is that just avoiding the issue all together?


Does data governance have a PR problem?

Jonathan Reichental: (30:43)
This is a conversation I have in multiple topics. My strength has been for a long time in the smart city space, the smart sustainable community space. That's where I really carved out a niche, but now my expertise and what I'm doing is much broader. But I would hear a lot from city leaders and all sorts of stakeholders that, "Can we not use ‘smart city’ as the term? It's turning people off. And are we a dumb city and now we're a smart city type thing?" And there's lots of jokes about that.

And the reality is the market will often give the title, and you kinda have to go with it. You don't get the opportunity to redefine the words whether you like them or not. You could argue about the designation of “metaverse” or “blockchain”. These words are maybe poorly chosen.

Jonathan Reichental: (31:29)
I think there are gonna be people and companies that despise the term “data governance.” Governance itself has this aura of negativity. It sounds like bureaucracy. But we're stuck with it. It is what it is. What are you gonna do? Right? I love the idea that within a business, you could call it in your internal branding, data enablement. That's beautiful. But the topic is data governance, and it's gonna be like that for the foreseeable future.

Satyen Sangani: (31:55)
Yeah, and you can use whatever euphemism you'd wanna use, but you sort of get there. Are there new policy types that have come out to play or are there new things that actually people are doing in data governance or what are the trends of what people are really focused on today that they may not have been focused on 3 to 5 years ago?

Jonathan Reichental: (32:11)
As we enter the 3rd decade of the 21st century, the organization leaders aren't waking up and saying, "I'm gonna spend all my time today worrying about and spending my energy on that defense-of-those-back-office things," right? That's actually a poor use of a CEO if that's how you go about your business.

But what you wanna do is come to work every day and figure out, "How are we gonna create better products? How are we gonna reach more people? How are we gonna grow our market? How do we continue to be relevant?" And if you're not building operations and approaches to that, it's not going to be as valued. And what I say in the book very clearly from start to finish is this is all hands-on deck, data culture type thing, but it is driven by leadership need and the sort of the core focus of the organization.

Jonathan Reichental: (32:53)
If you're not a profit-driven business, I totally get it. If you're a not-for-profit or even government, a lot of it is about quality and building trust with data, not so much about growing markets. But if you're a private company and publicly traded, your goal is to increase shareholder value; data governance has a very big role to play. What's different today in the 3rd decade of the 21st century is the zettabyte era, where you have more data of more value than ever before and we have more tools. The tool set is much better. The engagement of artificial intelligence, for example, in data governance as a real phenomenon today is a game-changer: finding patterns for you, being able to make sense of the signal and noise, as they say. All of that has elevated capabilities within the data governance space, giving leaders more tools, more capabilities to drive that offensive capability.

Jonathan Reichental: (33:40)
So I think actually, it's a theme in the book. Although the book cover is comprehensive, I'm very clear right through the end that if you only approach data governance as those back-office things, I don't think that's a winning argument, that the winning argument is to say, you get that, that's really key, that's your baseline, but the real value in data governance is innovation and growth.


From smart cities to data governance

Satyen Sangani: (34:08)
So some element of crawl, walk, run, and some element of also making sure that you have your goals well specified.

Let's move a little bit to the other topic where you have maybe as much if not more expertise, which is smart cities. You've written that book I guess I'll assume primarily based on your experience as the CIO of the City of Palo Alto. I've heard that term a ton, but I don't think I could ever describe for anybody what a smart city is and which cities are smart and which cities aren't. Can you tell us a little bit more about that topic and how that ultimately led to the bridge to why that got you to the world of data governance, but I'd love to just understand what a smart city is in the first place.

Jonathan Reichental: (34:39)
It requires a little bit of context building. It's 2023, the world is majority urban. Okay, so we think we're at about 60% of all humans who live today live in a city. This is pretty new. Before 2008, it was like 41% rural. I wanna say 51% rural, 49% urban. So we've shifted now to be an urban planet. And if you look out over the next few decades, we're growing our cities by about 3 million people per week. We'll add about 2 billion more people into our cities by the middle of the century, and by the end about 80% of all humans will be born and live out their lives in a city context. So in terms of the 200,000 years of homosapiens, the city phenomenon is like just in the last 10 years or 20 years. So it's pretty new and it's happened fast and it's a very big deal. Because what happens in cities?

Jonathan Reichental: (35:29)
That's where you work. That's where you have your home. That's where you get your drinking water and your food and your healthcare. It's where we are generating a lot of carbon, so cities are the biggest contributor toward climate crisis if you believe the scientific consensus. And if you look at many cities around the world, they work pretty good for what they do, but they fail a lot of people, and they fail on a lot of levels.

Just take something like transportation. I have the pleasure, much like you as an executive, to travel around the world and visit lots of cities. And one thing that you'll see a lot is traffic. If it takes an hour and a half from the airport to a hotel to downtown in the city and it's only 12 or 15 miles, I would argue and I think no one would disagree, that's failure. We've failed.

Jonathan Reichental: (36:15)
Our road networks, our infrastructure has failed and is increasingly failing. Take another example, which is energy. As cities grow and people use more electricity, our appetite is increasing, and if we continue to harvest coal, gas, and oil, we know where that will lead to. That's not a good future. We need to transition to renewables and non-carbon energy, things like solar, wind, geo-mass and others, and we're doing that actually. We're doing it at a rate that most people would be surprised about the rate at which we're converting and deploying new gigawatts of energy. It's all happening in a city context.

And lastly, I would say a lot of people's experiences living in a city when they deal with a city issue like getting a permit or recording a crime or wanting to get their road fixed or something, it's pretty bad. You often have to go to a place, fill out a form, figure out who to call. It's just ugly.

Jonathan Reichental: (37:06)
And this is in a world where people would rather use their smartphone to do most of their services because that's what they do in their private life and when they're working with non-government organizations. So all those things matter. We're in an urban world and cities need to think differently, and they have to solve problems differently. Without changing our decisions, without changing how we're doing stuff, the problem only gets a lot worse because it's accelerating. Urbanization is accelerating.

So smart cities are all about confronting those issues head on but with an innovation mindset, reinventing how we do stuff, and using technology and data to change the game, to completely shift how we've thought about these problems. For example, the digitalization of government. Government is also going through a massive global digital transformation right now. To give you just a dollar amount on it, by 2025, two-and-a-half years from now, the market's potential for digitalization of government is about $2.5 trillion — 2.5 trillion with a T.

Jonathan Reichental: (38:16)
And so that's creating a large volume of new start-ups and what we call gov-tech businesses. We’re also seeing the big tech companies, everyone from Microsoft to Google, to IBM and others really ramp up their government offerings by completely rethinking.

You have a new generation of city managers and mayors and council members who are now, they're internet native, they understand tech, and they can't understand that when they become leaders in government or they run for office, how poorly things run and how much is analog. In summary, the smart city movement is all about building cities that perform better using technology so that they can deliver better quality services to their communities and be more sustainable.

Satyen Sangani: (38:58)
In some ways there's some parallels, I think, between this kind of topic of data governance and this topic of smart cities, or at least I'm seeing some in how you narrate it. Do you think that's a fair observation? And what do you think is common between the two?

Jonathan Reichental: (39:12)
I do, I absolutely do. Data is core to the functioning of good cities, and if you think of a client base for data governance and data management, cities and governments, this is probably one of the biggest around the world. Clearly, private industry is a big opportunity, but I think government is the bigger opportunity, frankly.

Jonathan Reichental: (39:35)
Because they store and manage vast amounts of data, like colossal volumes, and they don't do it particularly well, and they don't secure it particularly well. I say that with great love for my city colleagues. Great love. But you only have to look at what happened to Baltimore and then Atlanta and cities all over the world where hacking and ransomware happens all too frequently, where city leaders don't have data to make good decisions. They use bad data, we just have terrible results in a lot of our cities.

There are great outliers from amazing cities doing great work, but the use of data in a meaningful way — both the management side and the governance side — is poorly executed in our communities today, but represent a phenomenal opportunity for training for vision, for tools and done right can make a big difference to our communities.

Satyen Sangani: (40:28)
Yeah. And the idea of a smart city, I guess, presumes that there is a smart way of doing things, and that other cities have discovered what works and what doesn't work. I can imagine that in the world of cities — ironically also true in the world of data governance — there are probably many cities who are like, "No, this would never work here. We do things differently, our culture is different, our people are different." And I certainly hear that about data governance: "Oh, these policies completely have nothing to do with us. We're very unique." When does one know where you should learn from best practice versus what's truly idiosyncratic to you and how do cities navigate that?

Jonathan Reichental: (41:10)
Well, one thing I've learned working with cities on every continent all over the world, is there isn't a playbook. You go in and they say, "We're having trouble," and you say, "Here's the answer for you." That doesn't really exist. There are themes, and I kind of used the themes at the beginning of my little pitch here, there's transportation, there's energy, there's digitalization, there's sustainability, those are four big themes. But when you kinda go a little deeper, stuff that matters to cities is very local, and so you have to go in and figure out all sorts of dimensions like culture, community culture, the geography of the city, the finances of the city, the economics.

Jonathan Reichental: (41:49)
There are a lot of different things that come into play when you think about how do we build a smarter, more sustainable community. And what problems are we trying to solve. So my book, Smart Cities for Dummies it's been received really well, tries to be comprehensive, and it does give a lot of examples, but it also recognizes that strategy is really important and the principles are important, like innovation, data use, and making the things that are important independent of where you are and what kind of city you are where I can bring value. And then if you wanna actually make the change and bring me in to help with that or any type of organization, then we're gonna have to get into the weeds. Figure out the specifics.

Satyen Sangani: (42:30)
Yeah. That idea that there's no playbook is interesting, it feels like a huge opportunity in both domains. You mentioned crypto, maybe just to touch on that, are you thinking of working on a For Dummies book for crypto? Is that in the offing?


Cryptocurrency and blockchain

Jonathan Reichental: (42:42)
I'm not doing a Dummies book, but I can tell you I have a book coming out called Cryptocurrency, which is the equivalent of a Dummies book, it's about a 400-page book on the past, present, and future of money. It's a comprehensive guide on the topic. It's not an advocacy book, I'm not a champion or promoter of crypto, I'm an educator on crypto, and the purpose of the book is to help everybody understand: What is this? Is it actually a Ponzi scheme? Or is there something to it? I give you the facts. You make up your own mind. So yeah, thank you for asking the question.

Satyen Sangani: (43:16)
Oh come on, you have to have an opinion, in the stream of global revolution to Ponzi scheme, having done 400 pages of writing, what is the answer to that question? Because I feel like, sure, you have people who are equally rabid on both sides.

Jonathan Reichental: (43:29)
You do. And unlike the topics we've been talking about so far. This one is polarizing. There's extreme views actually. And it's fascinating why that is, that actually really makes me curious.

I can say a couple of things, high level. Firstly, I can concur that any participation in crypto, whether it's trading cryptos or tokens or NFTs, those types of things, highly risky. I can first say that without a doubt, so enter at ye own risk. There is no foolproof way of getting in, making money, and getting out. Highly risky... So I wanna say that from the outset. Do I believe there's a future for cryptocurrency?

Jonathan Reichental: (44:07)
My answer is yes. I don't think as many people who are deep in this topic suggest that this is a novelty and it burns out after a few years, it'll crash and burn and it's completely nonsense, I don't take that perspective, I don't feel that through my research and work, that's the evidence that I see. There a room for a lot of perspectives, by the way. Respect all perspectives in this. It's very early. It's a moving target. For sure. As you can see, I'm really trying to be noncommittal here.

Satyen Sangani: (44:34)
Yeah, this is very diplomatic.

Jonathan Reichental: (44:34)
It is very diplomatic. Look, it's a fair question to say, what's my point of view. And I have to say that I do think it's here for the long term and what shape it takes and who dominates in the next five to 10 years, I think is very open, I think we'll see some surprises about what takes and what doesn't, and it's a compelling topic. There's the crypto part and then related is blockchain, which I think is a completely different conversation. But that is also really fascinating to me and we're early, we're early too on that.

Satyen Sangani: (45:05)
Yeah, before you take us out, give us 1 prediction about the world of data governance or 1 expectation that you have for it based upon everything that you've learned over the last couple of years in researching the topic.

Jonathan Reichental: (45:24)
I think probably a few years ago, having been involved in this topic, to create this video series and doing some talks and things on the topic, it felt still like kind of a niche topic, maybe there was a very small group of progressive organizations that really got it and were moving forward. My prediction is that this moves and has already moved, but is moving more aggressively into the mainstream, and within a few years, it's not a matter of whether you should have a formal data governance program, but the fact that you will have some form of it.

Jonathan Reichental: (46:03)
And that will be in all types of organizations. When you think about reporting requirements, particularly for public companies and what's required overall in reporting good operations, I think there'll be more demand on data governance results that we don't see today, but we really see more responsibilities relative to cybersecurity for the C-suite and public companies. We also see more requirements now emerging out of sustainability and diversity, having to begin to be reported. I think it's not the most “news flash” kind of answer, but the movement of the topic into the mainstream and much broader adoption, I think is right ahead of us.

Satyen Sangani: (46:42)
Well, hey, I obviously agree a bit. Given what we do here at Data Radicals. Great to meet you, again, and thank you for taking the time. It is a really fun book and I have not made my way all the way through it, but I have progressed through it quite a bit, and it's been really clarifying. Really excellent work. And thank you for taking the time Dr. Reichental.

Jonathan Reichental: (47:01)
Thank you very much too. I'm honored that you would read it. And it would be helpful to you in your role as CEO of Alation. So thank you very much.

Satyen Sangani: (47:20)
When attacking a hard problem, I often find that it's helpful to come back to first principles. Break it down into its most essential parts and then build it back up again from there.

Often, we do data governance because we have to, or because someone else did it that way, or because that's the way it's supposed to be done.

However, if you approach data governance — often a very confusing topic — with lazy thinking, you're likely to come up with a very confusing output. People won't know the goals, and it's pretty likely that you won't be successful.

So, being a dummy about data governance can be pretty useful! Start with the why, break the initiative up into critical parts and just ignore the rest. Jonathan's Data Governance for Dummies gives you the framework to do just that with helpful tips to guide your journey along the way.

Thank you for listening to this episode. And thank you, Jonathan, for joining. I'm your host, Satyen Sangani, CEO of Alation — and data radicals: stay the course, keep learning and sharing. Until next time.

Producer: (48:26)
This podcast is brought to you by Alation. The role of Chief Data Officer, CDO, is more vital and challenging than ever before, Alation offers a vision for building a strong data culture that empowers people to find, use, and trust data. Download the white paper The CDO's Toolbox, Seven Tips for Building a Successful and Sustainable Data Culture.

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Ashish Thusoo

Ashish Thusoo

Founder of Qubole and Creator of Apache Hive

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