Netezza Chief Talks About “Formative” PTC Days, IBM Deal History, and the Future of Big Data

The name’s Baum. James Baum.

OK, he might not be a dead ringer for 007, but I get the feeling Baum could handle himself in a firefight, high-stakes poker game, or dinner with the Queen, all with equal aplomb. He is a highly skilled pilot. He’s also pretty good with business intelligence, data warehouse appliances, and “big data”—all of which sound like tools of the trade for any self-respecting spy.

Except he’s not a spy, of course. Baum is the president and CEO of Netezza, the Marlborough, MA-based business analytics firm that was snapped up by IBM for $1.7 billion last September. He has helped lead Netezza since 2006, so his experience includes taking the firm public (in 2007) and managing big teams through tough economic times. He also has a unique perspective on building business software companies over the past couple of decades, working on startups in the dot-com era, and fending off competitors in crowded spaces. (He talks some pretty good trash about these competitors too, as you’ll see towards the end of this story.)

I sat down with Baum last week to talk about the IBM (NYSE: IBM) deal and integration, but also about his broader tech experience and the dramatic rise of big data. Lately, the term has become a buzzword for the skyrocketing amounts of information that businesses are trying to harness to better serve their customers. The field is certainly hopping in Massachusetts, as evidenced by EMC’s acquisition of Greenplum, Hewlett-Packard’s purchase of Vertica, and, of course, the Big Blue-Netezza deal last fall.

“Big data is here to stay,” Baum says. “This is a really important trend in the technology industry. There’s still a lot to be done. We haven’t figured all of this out yet.”

If you don’t know big data from pig data, don’t worry. Baum, 47, is adept at explaining its significance to experts and novices alike. He grew up in Burnt Hills, NY, the son of a Skidmore College professor and the head of a hospital nursing department. Baum studied engineering at WPI in Massachusetts and RPI in New York before starting his career at Boston-area-based Parametric Technology Corporation (PTC) in 1989. And that’s where things got interesting.

(In case you were wondering, PTC (NASDAQ: PMTC) is the computer-aided design and product development software firm that grew into a billion-dollar giant in the late ‘90s, slipped in the early 2000s, and is back to raking in $1 billion in annual revenues since 2008. It’s one of the underrated success stories of the Boston tech scene.)

Read below for Baum’s deeper insights and perspective on big data and business intelligence, as well as broader lessons for entrepreneurs and executives. I’ve edited the interview for length and clarity:

Xconomy: So tell me about your early career and how it shaped you.

Jim Baum: It was an interesting time in 1988. The tech industry as we understand it today was pretty young. It was a very formative time, with Data General, Digital, and Oracle was just getting going. I went to a small startup in Waltham, called Parametric Technology, or PTC. Sam Geisberg started it in 1985 with $50,000.

I joined PTC in 1989 as employee 95. It was a great, great experience. I worked for some of the best leaders I’ve ever met. I was there 11 years. The company went public [in 1989] on about $11 million in revenue. We had 40 quarters of growth in earnings and revenue. It was a rocket ship, an amazing culture, an amazing group of people—amazingly smart, talented, young entrepreneurial people who really knew how to get things done, with tremendous leadership.

I say that because it was very formative for me. That was my MBA. I don’t have a formal MBA—I earned it at PTC. And I learned it in a variety of roles. I started out as a field-based engineer working with customers on the application of the technology. If you remember the original Motorola flip phone, the big square thing that flipped open, we did that. That was one of my clients, we were working on the program for developing that thing. There were some funny stories about it. The reason it looked the way it looked was not because the industrial designers wanted it to look like a brick, it was because that was the capability of the [design] software at the time. Obviously the [computer-aided design] technology has come a long way.

In most tech startup companies, and PTC was no exception, the founder is the product manager. And he’s also sometimes the CEO, and the VP of sales, and everything. At PTC, Sam was the technologist and the product visionary. Therefore he very closely controlled the product. Not long after I started, we had released a new product, and it was terrible. Sam was somewhat intimidating to most people—he was a tough guy, very smart. (We just had a retirement party for [former PTC chief executive] Dick Harrison, and we took a poll in the room of 40 people, “How many of you have been fired by Sam Geisberg?” Like 80 percent of the room raised their hands. He’d get mad at you, call you an idiot, he’d fire you, and then he’d go away. But you’d come in the next day, and you’d walk down the hall, you’d see Sam and you’d say good morning, he’d say good morning, and you figured everything was OK, so you just kept going.) One day he asked me to become a product manager. The company’s first product manager. It was an interesting and lucky opportunity.

X: What did you learn in that job, specifically?

JB: I think product management is the best job in the company, because you get to see everything. You get to steer the direction of the product, analyze and understand the market, fit the product to the market. You’re close to engineering, close to sales, close to marketing. It’s a wonderful place to learn how a company works, how a market works, how a technology works. I did that for quite a while, and that job of initial product manager turned into the job of managing all of product management for the company.

I went on to other roles, I managed marketing, managed engineering, was a general manager for a while. For the last couple years I was the general manager and executive vice president of the Windchill program—it was all about enterprise information management for product development companies. We were instantiating a vision around a complete suite of data management and applications around that infrastructure to deal with every aspect of product development. We built that business based on an acquisition of a competitor in 1998, Computervision. It was an enterprise software role. I did that for two or three years. Then I left and went to [e-commerce search startup] Endeca.

X: So the dot-coms were calling you…

JB: It’s killing me. This is the year 2000. The bubble’s about to burst. We’re feeling like we’re standing outside this window with our noses pressed to the glass, there’s this great party going on inside, and we’re not invited. Here we are, a billion-dollar revenue company, and has a higher market cap than we do with 18 customers and a trick duck. It made no sense whatsoever. It was frustrating for a lot of companies in that era. The basic economical principles seemed to no longer apply. And, of course, that proved to not be the case over time.

It was an allure for many people to leave an established enterprise technology company and go try their hand at a startup or become part of a startup. The bubble burst at exactly the time I went to Endeca. I joined in summer 2001 and we were raising money. Steve Papa had founded Endeca, and they were doing OK, maybe 20 employees. We were closing that series of investment on 9/11. I stayed there for five years. We built the company from the ground up. When I got there, a lot of the technology heavy-lifting had been done. They had built the product but they hadn’t quite found the market for it. We had to go and find the market, move the technology into the market, find the value proposition, build a sales force around it, build a marketing engine around it, finish the product for various use cases, and build a company. That was a tremendously fun activity. I joined as the COO, and left as the CEO.

X: So now it’s 2006. What brought you to Netezza?

JB: It was founded by Jit Saxena in 2000 with Foster Hinshaw, who went on to Dataupia. Netezza had built a remarkable technology. It had some great technologists, a lot of real in-depth enterprise, big-scale complex systems experience, and a very interesting blend of hardware and software—what we call an appliance today. The data warehousing market was very well understood. The existing technologies were very complex, expensive, difficult to deploy, very long time to value, and increasingly unwieldy and slow. There was lots of end user resentment around [business intelligence]. Data warehousing had sort of become a dirty word; it was not something with which you could easily succeed. The competitive landscape was Oracle, Teradata, IBM, and a bunch of little companies. But to this day, primarily our competition remains Oracle. And we’ve made a very conscious effort to go after Oracle’s weakness in this particular aspect of database processing: their stuff is very expensive, very slow.

We [at Netezza] were able to demonstrate orders of magnitude—10, 100, 1,000 times—better performance, in a system you could deploy in days, not months or years. You could get value from it quickly, and you could scale.

X: So where did all this “big data” come from, and where is it going?

JB: Big data has become an interesting buzzword in the industry, but what is it, really? Look around at what’s happening in the world. Data collection is becoming ubiquitous. I drove in here from Natick, I went through two toll booths, I made five phone calls—I produced a pretty big data trail on my way here. I logged into the Internet this morning and went to three news websites, all of which I have subscriptions or logins or cookies for. I met with a buddy for breakfast who started a company that has this very cool online coupon technology that’s based on my preferences, who I am, what my purchase history is. It’s everywhere. We’re now talking about appliances that report back to the electric grid. We’re looking at sensors on every vehicle known to man.

A single rack of Netezza is a massively parallel grid of compute and storage nodes, linked in a special way. In 2006, we were in the process of building our first 100 terabyte machine. It was eight refrigerator-size racks, approximately 1,000 nodes of compute. I remember thinking nobody is going to buy a 100 terabyte machine. This is crazy, this is huge, right? Wrong. They sold like hotcakes. Catalina Marketing bought the first one. Today, in a TwinFin, our current product, a single rack can hold well over 100 terabytes of data with compression. We have systems running today with north of 1 petabyte.

We’re primarily focused on analytics around high-value structured data. Transactions, loyalty cards, customer data, credit card/financial data, healthcare records, call detail records in the telco industry. Take IBM’s Watson [the Jeopardy machine]. That’s a workload optimized system; behind the scenes it’s parsing through massive amounts of unstructured data. This is changing the world.

It’s not just about capturing and managing this data. That’s done. It’s understanding the knowledge from these data assets in real time, not just to understand history, but to understand the future. Predicting, and then optimizing based on those predictions, will have the most significant and profound impact on business that we’ve seen from the technology industry. It’s way beyond what ERP [enterprise resource planning] or CRM [customer relationship management] have done for us. These are the things that are going to help people make the killer decisions in business.

X: How did the IBM-Netezza acquisition come about? What’s the deeper history there?

JB: We partnered with IBM for a very long time. Netezza is a data warehouse appliance, a high-performance repository for large volumes of structured and unstructured data. It allows very high-speed access to query that data. It’s an integrated system of hardware and software.

In the world of business analytics, the ecosystem is how you get the data into [the appliance]. A Netezza demo without the ecosystem around it is just a black screen and you’re issuing queries. What really makes it come to life is the application that sits on top of it—either a business intelligence or analytics application (like MicroStrategy, Business Objects, Hyperion, SPSS, or Cognos). We’ve always had these partnerships that surround the company. Where does IBM fit? IBM fits all over; as they acquired Ascential, Cognos, and SPSS, we partnered with them over the years.

About three years ago, we made a decision on our platform that was quite important. Our product and its core benefits are derived from purpose-built hardware/software for data analytics and business use cases. We did that in the early days through developing massively parallel database software, and integrating that very deeply with proprietary hardware. We built this platform because at the time, we knew the general-purpose computing platforms were too hot, too expensive, too slow, to create a very high-performance platform. We also knew that at some point in the general-purpose computing platform, the benefits would exceed the liabilities. That point came about three years ago. So we made a very conscious decision to migrate the platform. We did a detailed review of the market, and chose IBM as our blade [server hardware] partner. We integrated the blade with a database accelerator card of our own—the one remaining piece of proprietary hardware that’s in the platform. We also worked closely on the storage subsystem behind it. We package all that with software.

It really deepened the partnership with IBM. IBM’s strategy around analytics, it starts from this “smarter planet” mantra that is appropriate for Super Bowl and prime-time TV ads, and it goes very, very deep with an extensive array of technologies and services across hardware and software that can deliver on this promise—all the data modeling, all the ETL [data warehouse tools], all the database technology, now the appliance technology with Netezza, the business intelligence technology, the business analytics technology, specific vertical applications for CRM like Unica. We always felt like IBM was a great partner. Of all the mega-vendors, they’re the ones who get it. They’re the ones who understand and are really betting a lot on this opportunity in analytics.

X: Talk a little more about the timing of the deal and the cultural fit between the companies. Why get acquired if Netezza was doing well?

JB: The timing was very good for both of us. The GM who sponsored the deal was Arvind Krishna. We had a lot of conversations about the opportunity and the vision of what could be. IBM is a high-integrity, honest, call-it-as-they-see-it company. Netezza has always been high-integrity, sort of familial, very focused on doing what’s right for the customer. We want to be a company that’s easy to do business with. That cultural fit was there as well. From Netezza’s standpoint, we had done very well. We did $190 million-plus in revenue last year, and analysts were saying $250 million-plus this year (it’ll be more than that).

Growth was there and doing really well, but as we looked forward, what are the inhibitors? Our business was 80 percent North America. IBM, their business is primarily international—they have a tremendous investment in the fastest growing economies in the world. They have all the distribution infrastructure, support infrastructure, all the market and brand presence. We’re now taking Netezza and, over time, will be introducing this technology and product to over 150 new companies.

Netezza was public, and we were managing to two things: EPS [earnings per share] growth and revenue growth. As you’re managing those, your ability to invest is constrained. You can’t satisfy everybody. We were doing well, growing at 30 to 40 percent a year. But IBM can do this really differently. And Netezza still exists—it is a business unit inside IBM, our customers still deal with us—but we’ve leveraged this massive asset to take and distribute this on a truly global basis. The question was always, what’s holding you back, why aren’t you growing faster? It’s access. It’s presence in markets where we are not. Well, we just fixed that problem. Now we’ve got IBM on our side, and we’ve got presence in markets we never dreamed of getting into.

We were 500 people when they acquired us. We’re over 600 now, and we’ll be over 800 by the end of the year. We’re in the process of doubling the Netezza sales organization. That’s the kind of investment I couldn’t make as a stand-alone public company.

X: Most tech acquisitions fail in the integration stage. What’s the plan for IBM and Netezza, and what are the challenges?

JB: IBM is a pro at this. It starts with a business plan. When they acquire a company, they have a well defined, well understood set of measurable business objectives. They expect to create a return on this investment. That’s step one. Then there are philosophical objectives—let’s not break Netezza. Let’s preserve that, keep it intact, and let’s grow it. They put a tremendous amount of energy and resources into defining how it gets integrated.

We’re heavily influenced by IBM’s business processes. They introduce one of their strongest executives—an integration and transformation executive—and pair them with me. Debbie Landers works the IBM side, and I work the Netezza side. There are thousands of issues [to discuss]. And there are integration executives for each function—engineering, sales, marketing—to help us navigate through the land of IBM.

Then there’s the accountability side—what are the problems, what are the issues, what are the hiccups. That’s reported on a regular basis. There is a culture and values executive who has interviewed senior management, done surveys, and helped people understand one another. This was an attractor back when we were considering doing this with them—they’re very focused on people. IBM is very focused on wanting to retain and motivate great people, and add great people to their company.

X: Let’s talk about the current competitive landscape in big data and analytics. There has been a lot of activity around Massachusetts in the past year, with EMC, HP, and others entering the market.

JB: When EMC acquired Greenplum, they were not a big company. Greenplum had been around for a long time and had started to find a niche in the market around high-scale, what I call queryable archive solutions. We’ve seen them playing the competitive game of cost per terabyte, a game we don’t tend to play. We tend to focus on value created through performance. They’re different applications. With EMC acquiring them, we’ve seen not a lot of change. The EMC sales force is in no way prepared to go sell these high-value data analytics solutions to their customer base. What they are prepared to do is recognize that they can exist—EMC has a very large footprint in storage—so they can see an opportunity. But the Greenplum sales force still has to come in and drive a transaction. So they’ve got a long way to go. We’ll see more of them over time. Greenplum is still out selling on non-EMC hardware, so at some point they will need to go through a major product shift.

Oracle is very active. They have been our number-one competitor since day one. They have the largest installed base in data warehousing. They are positioning their new product, Exadata, as a solution for online transaction processing, as well as for warehousing and analytics. We compete with them all the time. We have an extraordinarily high win rate in analytics. We don’t compete in online transactions. They’re putting a lot of energy and effort into developing a product that they’re positioning as all things to all people. The competitive dynamic is interesting. We like to compete based on a proof point. We want you to say, come in and prove it. We will bring our technology in and challenge the competitor, Oracle or Teradata, set it up, run it with the customer’s data and applications in the customer’s environment. We find the Exadata machine is very complex; it takes a long time to set up, tune, and provide value. With our appliance approach, you’re up and running in a day. We compete with them every single day, and we beat them handily in the analytics space.

HP—they missed the window. They’ve had a tremendous brain drain. They were failing with Neoview [data warehouse and business intelligence product]. They finally publicly terminated it. So guess what happens to all of the intelligence and knowledge around business intelligence and analytics at HP? They’re working for IBM or somebody else. HP re-announced a partnership with Microsoft around Madison to build an “appliance.” How you call this an appliance when you’re getting software support from Microsoft and hardware support from HP is beyond me. That’s a bundle, and it’s a bundle of trouble if you ask me. Because you’ve got multiple vendors to deal with. Then they go and acquire Vertica, but Vertica is smaller than Greenplum was. The talent pool is gone. HP has completely missed the boat on this.

X: So with all these giants stomping around, what are the opportunities for young startups in big data?

JB: There’s a lot of interesting stuff happening with Hadoop [an open-source platform for storing and analyzing big data]. We are seeing it become an important enterprise tool. There is opportunity to bring Hadoop to the masses, to make that technology more broadly accessible. In fact, we’re doing work with Hadoop inside the Netezza appliance today, so it’s part of our strategy as we continue to broaden.

There’s some really interesting stuff going on with open-source analytics that has the opportunity to offset some of the dominance of the big analytics vendors. We’re seeing many customers beginning to use open-source tools like R [language for statistical computing]. There are startups around it, sort of following the Red Hat [Linux] model. There’s really interesting stuff going on in solid state—SSD [solid state drive] storage is becoming important to big data. It’s still expensive and hard to maintain, and hard to build around. But it’s a really important technology and one that you’ll see us taking advantage of.

The other area in core technology that we’re seeing evolve is the use of GPUs [graphics chips] for some of the specific computational processing activities going on. There is opportunity there. Those are interesting spaces to watch.

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