Jaspersoft CEO: We’re driving pervasive business intelligence

Would your ears perk up if you heard there was a BI/analytics company that claims to deliver three-quarters of the functionality of traditional BI solutions at 20 percent or less of the cost?

What if you also learned that its product is fully cloud-based and can be embedded in Web and mobile apps? Or that its CEO promises to help you deliver BI beyond power users to virtually every employee, helping you foster a data-driven culture?

If all that sounds intriguing, meet Brian Gentile, chief executive of San Francisco-based Jaspersoft. In this installment of the IDG Enterprise CEO Interview Series, Gentile spoke with John Gallant, chief content officer with IDG Enterprise, and InfoWorld Editor in Chief Eric Knorr about how Jaspersoft aims to shake up the BI market and how big data will shake up everything. Gentile also discussed the embeddable analytics market and why some big-name customers are walling off the old-line BI solutions and firing up Jaspersoft instead.

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Q: What’s the mission for Jaspersoft, and what makes you different in the marketplace?

A: We create lighter-weight, entirely Web-based, powerful but simple, BI tools that can be integrated into business apps and processes. Many other companies take our tools, and we become their BI inside, the reporting analysis inside of their apps. Sixty-five percent of our business is embeddable BI. You know you’re using a reporting and analysis tool, it’s providing you with calculations, and some are aggregations and some are summaries, but you might not know it’s Jaspersoft.

We’ve had two axes on which we’ve innovated. The first axis is open source, and nine years ago that was really novel. We were the only BI company with a pure open source strategy. The other is the modern architecture. We’ve always said we’re going to deliver everything — every client experience — inside of the browser. All the heavy lifting is going to be done at the server, and it’s going to be a pure, open, Web-based, open standards-based server.

[Early on] that was a pretty risky call, because the client browser technology wasn’t really where we needed it to be to deliver an application-like experience. Today it looks like a really smart and bold call because of technologies like AJAX on the server and dynamic HTML and now HTML5, which is what our [latest] release is substantially about. It looks like a brilliant move because we have just as impressive an interaction model inside of our environment and animation and graphics and visualization of data, and we have scalability, low cost, same footprint regardless of the device that you’re on. Our cloud-based deployment is just as easy as on-premises. We have access to big data because the architecture never assumed it would just be structured in a relational world. All of a sudden our tough, gritty, hard-fought tradeoffs starting seven years ago look like brilliance.

Q: Let’s talk about this business intelligence inside processes and applications. Help me to understand how that plays out. Give me an example of what you or a partner is doing with that.

A: The fastest growing subsegment of BI is embeddable BI, and Gartner and others have been reporting on this for a long time, although there’s not a lot of clear understanding of what that means. It’s really a spectrum of embeddedness to a BI tool — everything from “let’s just stick a graph that we created in an iframe inside of a Web page” to building it into our portal, we want to expose this BI within our enterprise as part of a standard set of portal-based applications. Maybe the next stop is Web services. Now you’re getting a little more sophisticated and you want to be able to call the application and have it yield control to you and create a report or create a graph result or something like that in the return control.

We’ve identified five levels of embeddable BI, from the simplest to the most sophisticated or most completely integrated. We’ve published two documents on this over the years, one of which is like a how-to guide for the technologist. You’d be amazed at how many people today are actually embedding BI. It’s testimony to the fact that everyone’s building software again. The Web paradigm has created a new class of programmer and a new set of standards around which everybody programs. We see this explosion of development that’s based on the Web.

Q: Just to be clear, you’re not talking about ISV partners, you’re talking about enterprise application developers, that kind of thing.

A: Everybody you just mentioned and more. If I showed you a customer list by logo, I know I could point out which ones are embedded and which ones are not, but you wouldn’t be able to. So, yes, it’s a lot of ISVs. Yes, it’s a lot of VARs, who do solutions-oriented work, and SIs [systems integrators], but it’s also enterprises. It’s amazing the breadth of application development that’s going on today.

Q: Give us a real enterprise customer example.

A: I’ll give you a couple just to mix it up. DuPont has been a customer for years. They have plastics and paint and coatings divisions. It’s a tough market, low margin, typically. Part of the way they distinguish themselves is by making themselves easier and simpler [to work with] for their supply chain and their demand chain. They’ve created a set of applications that are portal-based that their supply chain partners can log into. One of the views is an analytic view that shows the status of a wide variety of parts and components and pieces within their overall supply chain. They do this as an effort to more closely knit together the supply chain with the demand chain. They don’t charge for it, they just see it as a competitive advantage. Jaspersoft for years has been the analytics inside of all that.

Several of the world’s largest investment banks are using Jaspersoft for their own funds transfer supply chain — it’s a parallel to a supply chain but for a banking or investment institution. They’re using a similar set of reports and analysis along the whole supply of funds transfer from source of funds through to use of funds and movement of funds through that chain. They report on it and analyze it and they provide those views to all those partners. Some are inside the bank, some are outside the bank. So they have to have a secure login, probably a single sign-on or authentication.

Q: Who do you consider to be competitors in this crowded BI and analytics market?

A: There are so many competitors we have to put them into categories. Let’s start with the best-known, the large-cap, probably-already-been-acquired, household-name guys: Business Objects acquired by SAP; Cognos acquired by IBM; everyone else acquired by Oracle. As we’ve matured and our feature set has advanced, we run into them more and more commonly. There’s opportunity for us because the kind of price tags that those guys are still commanding makes it compelling for a CIO to say, ‘Wait a minute, why am I paying all that?’ Against that kind of competition at any scale, meaning hundreds of seats or thousands of seats, we would be 10 to 15 percent of the cost of those guys. That’s compelling.

In fact, the bank example I gave you earlier, that particular bank is trading out a big competitor systematically over time for the broader use of Jaspersoft because there’s a not quite 10-times advantage in savings in so doing. They aren’t going to completely move Business Objects out, but they’ll ring-fence it and be done with that level of cost and complexity. For new projects where Jaspersoft is a solid fit based on our features and capability, they’re going to use Jaspersoft because the cost-value curve is so compelling.

Q: Those big guys typically have their own integration arms that customers employ as well.

A: It is true. There’s a whole industry around those guys. That adds both to the value and the complexity at the same time. They’re seen as safety because of the industry around them, but the complexity factor is clear. You’re probably not going to choose one of those older tools if you say you’ve got a problem to solve and only six weeks to solve it. You look at a tool like ours that you could download in the morning, and if you have somebody pretty smart, you can be analyzing data in the afternoon, and it could be from almost any source. It’s a pretty big difference.

Q: Who are the other competitors?

A: They’re very different. Second would be the faster-moving, higher-growth, newer players that are typically referred to as “data visualization” and maybe “data discovery.” It’s specifically QlikTech and the even newer Tableau. This is the first group that I actually have a reasonable amount of respect for, because they’re doing something interesting and disruptive. For a certain BI audience, they’re doing something interesting and productive and disruptive. They’re providing the business analyst, the power user, with a genuine alternative to both the old guys and Microsoft Excel. If you’re a data jock and your job is to live inside Microsoft Excel for a lot of the day and along comes QlikTech or Tableau, you’re pretty excited, because this gives you a whole new, really interesting visualization route. Download, connect, it interrogates the data, allows you to discover it quickly and start visualizing it. Fantastic. What’s not to like?

A couple of things: First, the architecture. Both of those products and companies have chosen, for very good reasons, to use desktop-centric code. Both products require Windows as your desktop environment. What if I’m not on Windows? You don’t get to play. Now they’ve made mobile extensions and so on, these are smart companies.

But fundamentally, the architectures are Windows-based, and Qlik is even more difficult because it has a variety of different code bases over the years. It’s actually a 20-year-old company. Tableau is only six or seven years old, so they have a more modern environment, but it’s still Windows-centric. And it’s inherently designed for that data analyst. It has a lot of things going on and if you’re that data analyst you love it.

But what if your job isn’t to be a data analyst? Tableau is probably not a great fit. It’s probably too much, and in fact if you wanted to scale Tableau to hundreds or thousands of desktops in an enterprise, a) it would be a poor fit because not everybody needs a Tableau, and b) it wouldn’t be cost effective. You’d literally be putting Windows code on everybody’s desktop and paying for it. They have a workgroup server edition, they’ve done some nice things architecturally to make it a little bit more scalable, but it’s not designed for 100,000 desktops. You would never think of Tableau for that or Qlik.

While we respect them, we respect them for the user type that they have been designed for. Fundamentally, they’re not scalable, and they’re not going to have a very broad impact on how many people in an organization are really using BI to get their job done.

The third category is a whole bunch of niche vendors that on any give day we might bump into. Most of them are very small, much smaller than Jaspersoft, and they solve for something that’s industry specific, vertically specific, or a certain BI function like dashboarding or just graphing. So they solve some very niche-oriented thing.

Q: There’s been a lot of money been spent on BI over the years and there’s really not a lot of customer satisfaction to go with that. How do you change that for customers?

A: You could say that Qlik and Tableau have done a great job changing their portion of this curve by appealing directly to the business user. If you queried those business users, you’d find a pretty high level of satisfaction. If you queried the IT guy who has to kind of clean up behind them, you might not be that happy. We believe satisfaction and broad use of BI come by bringing both the technologist and the business users together. If you’re going to reach the number of people, devices, desktops, whatever, in an enterprise it’s going to be because you’re delivering to them just the right amount of BI at the right place, the right time, no more, no less. That’s not Tableau. You’re not going to be able to tailor Tableau for the amount of BI that somebody on a production line needs versus somebody who’s a data jock.

With Jaspersoft, that’s exactly what you get. You get a tailorable, implementable, customizable amount of BI that can be constrained for the type of user that needs it. They could get a report, just a report, delivered to them that’s interactive, they can explore the data within that report and it can be delivered to them on whatever schedule you want, and it’s delivered entirely inside of their Web browser. You don’t have to install or manage anything. It’s consistent whether it’s on a mobile device or a desktop computer.

The technologist who’s setting it up on behalf of that end-user is saying that user only needs this type of data and this type of dataset; I don’t want to confuse them with a lot of other things. I want to give them an explorative environment, but it’s constrained based on that report dataset that’s now delivered to them in the context that they need. That’s very different than a power user who might need our full multidimensional analytic environment, which by the way is delivered in that very same browser with the exact same techniques, just a lot more capability, all exposed through HTML5, all scalable. The cost-value curve is identical, there’s just a lot more functionality exposed. That person appreciates that functionality because they know what to do with a pivot table.

Q: So it’s one license for all this technology. You use different parts of it in different parts of your organization depending on what the roles are?

A: This is correct. How do you reach a very broad audience, satisfy them so they are having a great BI experience and, more important, helping to ensure they make decisions based on data? That’s fundamentally what the BI equation has missed for the last 20 years: how do you get to the 85 percent of the organization that’s been forsaken with BI? How do you reach them with a tool that is context sensitive, delivers just the right amount of BI, within an environment that’s comfortable to them, that’s affordable? Anybody who doesn’t understand that is really missing the boat. If you’re going to deliver BI to 100,000 employees inside of Procter & Gamble, it’s got to be affordable. No CIO in his right mind is going to deliver something that’s tens of millions of dollars. That’s the mission we’ve been on for seven years, and that’s what distinguishes us. I don’t know anybody else in BI who’s after this mission.

Q: SAP provided a significant chunk of your funding?

A: They are a multitime investor who began their investment in about 2007.

Q: So you listed them as a competitor. Why would they fund a competitor?

A: They actually made their first investment in Jaspersoft just prior to the acquisition of Business Objects. But I believe that even if they had acquired Business Objects and Crystal Reports as part of that acquisition they would have made the investment anyway. Why? We’re fundamentally different. Anybody who’s evaluating Jaspersoft versus Business Objects has probably made a mistake somewhere along the line. It was a good investment before or after that acquisition because we’re solving very different BI problems.

Q: Going back to the big guys, how would you compare the depth of analytics capabilities you provide versus the traditional players?

A: Seven years ago we made this decision to deliver everything inside of a Web browser, and that was a fundamental constraint, especially back then. It is still today, but less so.

The other companies with which we compete mostly are many years older than us, and they got quite a head start in building features and functionality. Our goal today is to deliver a very high percentage of the features and functions at a fraction of the cost. Our goal is to provide 70 to 80 percent of functionality, the vast majority of what anybody really needs in that level of BI, for 10 to 20 percent of the cost. We believe that for a lot of use cases, customers are going to say, “I’ll take that.”

Similarly, in the visualization world, where you’re talking about visualizing a lot of data very quickly and easily, our goal is to provide 70 to 80 percent of Tableau at 10 to 20 percent of the cost and deliver it entirely inside of a Web browser, fundamentally changing that cost curve as well. In fact, there’s a percentage of functionality that we don’t even want to go to. I mean, I don’t know if it’s 20 to 30 percent, but I don’t think I ever want 100 percent of the functionality. Because like Microsoft Word, such a small percentage of the audience uses it, and it makes your product so much more complicated that I don’t want to go there.

Q: How does big data change the market for you?

A: Big data changes a bunch of things, and it’s so important that I’ve said in a few years we’ll just call it data again, because it will be so primary, so elemental. Being able to analyze variable data types at a higher speed, higher velocity, is really important. The fact that there are bigger volumes of data isn’t so important, it’s really about the variability of data, new data types, and the velocity at which they must be used before the data goes stale. Those are the two distinguishing characteristics of big data.

When we built our server architecture starting seven years ago, we never assumed that the world would be full of exclusively structured relational data. We always knew that data would have greater variety rather than less. So we made it easy right from the very start to connect to, and analyze or report on any type of data. When these big data types started to become more pronounced in the last three years, we’ve been the first to not only embrace them, but make tools available, connections available to them natively, so that you can really exploit them.

Our first connector into what was little known as Hadoop back then used both Hive and HBase. We even dabbled in HDFS and Avro back in the day, not knowing what customers would prefer. Now we have not only all those different pieces of Hadoop as framework software, but we have all these different NewSQL and NoSQL data types. We have advanced our connectivity and intelligence into these relatively abstract data types. We need to connect to these and treat them as if they were structured and relational, with enough intelligence. We’ve made these native connections available — and by native I mean directly from our BI server, you don’t have to use our ETL [Extract, Transform, Load] tool. ETL is another option, and it’s a prominent option for a lot of customers, but you don’t have to use it because ETL introduces latency by definition.

Q: How does using unstructured data change the users and usage of the product?

A: Maybe the most encouraging thing about the whole big data movement is that it will force the business side and IT to come together. There’s no way you can create a really compelling application of big data without the two groups working in concert. The domain knowledge that comes from the business side is the catalyst. The domain knowledge is what’s so vital. They need to know what data exists out there, if it can be properly structured and analyzed what business insight it would yield and what advantage would be possessed by the company.Business has to drive this.

These technologies are not straightforward. There is a lot going on here, and anybody who tries to oversimplify it is doing a disservice. It requires a technologist to sit down, whether it’s Cassandra or Mongo or Couch or Volt or any of the others, or Hadoop … that’s a fundamental decision that should be made between both the business users and the technical team. The choice there is elemental to whether or not you’re going to be successful.

The biggest mistake we see in big data projects is the underlying data source technology is mistakenly chosen. They choose Hadoop because that’s what they know or they’ve heard of, when it really would have been better to use a document-oriented data store or a key value store. Now they’re in a corner, and they look like they’re failing, but they wouldn’t be failing if they had just started by asking what the business requirements are. What amount of latency is acceptable? What type of data? Now it’s just more important — because the volume is so much greater and the business insight can be so much more valuable — to bring business and IT together to make the right fundamental choices. It’s really a powerful time again in this world of data and BI, because it’s another fundamental reason that the two teams have to sit down and come to agreement and think about this from one viewpoint rather than mixed viewpoints.

Q: What about real-time analytics?

A: It’s an overused term. I mean, “real time” means something different to different groups. If you’re sitting down with a business audience and they’re trying to solve a problem, they might call something real time that has a three-second delay in the data from capture to display. Technically that’s not real time, but for them it’s real time. I just try to be precise about it. Real time literally means there’s zero delay, and there are very few applications of that. It’s not good or bad, it all depends on the business application.

Q: You mentioned your latest release, 5.0. What’s new and great about it?

A: It builds on this foundation that I’ve been talking about. Cloud-based BI, which I didn’t mention, where we exist in the cloud today and all the major environments, whether it’s the Amazon Web Service Marketplace or Cloud Foundry or Red Hat’s OpenShift. We have made announcements with all those and more. We’re in the cloud. We’ve been in the cloud longer than anybody. We’ve been doing the big data dance longer than anybody. Our architecture has adhered to all this, and we want to amplify the architectural choices we’ve made to the benefit of our customers. Everything must continue to be in the Web browser, everything must be server-based and scalable, at Web proportions, and affordable.

Version 5 brings together a vision we had three or more years ago. It’s just that HTML5 wasn’t available then. We started playing with the early versions of HTML5, but it wasn’t anywhere near ready for usage. Now, Version 5 brings together a brand new graphing and visualization engine that is entirely built on HTML5. That gives us a level of interaction, animation, and visualization inside the Web browser that would be very similar to a Tableau-like experience, and we’re just starting. So the first major feature is a consistent and high-performing visualization engine that’s entirely built on HTML5.

It lets you build beautiful animated charts, with all sorts of interaction, mouse over, feedback, zoom in. We built a new tool we call the dimensional zoom tool, which looks like a slider bar, and when you slide, it’s like zooming in on a camera. You’re actually zooming into more detail on the data, exposing more dimensions technically. When you zoom out you’re aggregating, or summarizing, fewer dimensions. Remember my spectrum earlier? For some percentage of end-users, this is data analysis. All you’re doing is providing a highly interactive visual experience inside the browser, and for them, they’re analyzing data. It’s not OLAP, but it’s for them analyzing data. For another user, we’ll provide them with that same experience wrapped around an OLAP on the back end. So they’re getting that same beautiful visualization, ability to explore in a cross-tab environment, they’re charting it, and it’s identical, it’s just a different, very rich underlying dataset.

Data virtualization is number two. We’ve built a complete virtualized data environment that allows you to leave the data where it is, in all of its various sources scattered across the enterprise, but structure a query using our virtualization engine that goes after all that data, pulls back the results, aggregates and displays the results in-memory for the user to explore inside of that visualization environment I described. In fact, we have the ability to describe that virtual data semantically. We have the ability to capture metadata about those virtualized data sources. Not only can you do what I just described by leaving the data where it is, but you can express those data views in English-like terms, where a novice user can now drag and drop on a canvas their own reports that are built on these virtualized data views, not knowing or caring where that data actually exists. Maybe there’s some from Hadoop, maybe there’s a bunch of stuff in Cassandra, there’s an Oracle database, there’s a Teradata warehouse, whatever, and all those views are being aggregated by our virtualization engine, expressed in English-like terms, visualized in an in-memory engine that I’m going to get to as my third feature. But that’s data virtualization.

The third feature is the in-memory capability. We’ve long had an in-memory engine. In Version 5, we’ve vastly expanded it. It’s our own columnar in-memory engine. It’s non-persistent, so it exists as long as the end user state exists. But what it allows is exploration of that data at memory speeds, and the dataset can be extremely large. With Version 5, that’s a full terabyte of data. If your server is properly configured, you could return billions of rows of data from any data source using that virtualizer technology, hold it in-memory, and express it inside of this visualization that I described earlier. All done at sub-second in-memory speeds because it’s all in-memory and it’s addressed with a columnar orientation.

The fourth is advancements to our analytic capability. If you are a power user and you want to use richer multidimensional analytics, we’ve increased the feature set, getting closer to that 80 percent, if you will. We’ve increased the mathematics behind it, the performance of it, and we’ve added the HTML5 engine I mentioned earlier so you get this consistent experience from one end of the product to the other for visualizing it. Out of the box, we provide a backend OLAP engine called Mondrian, which is open source, very capable. But some of our customers have investments in other OLAP environments, and one of the most popular is Analysis Services from Microsoft. Our tool now natively supports Microsoft SQL Server Analysis Services. You now can point our visualization environment, our analytic front-end at Analysis Services from Microsoft and you get the same results, the same front end experience, which is a pretty clever technique to help our customers maintain investments in those.

The fifth change is administration monitoring support, internal things we’ve done to make it easier to install, upgrade, and monitor the health of the server, which is really important if you’re an administrator. It’s not one of the sexier things we’ve done, but God knows it’s going to help a lot of customers. We’ve used our own tool to make our own tool smarter. We built a set of best practice dashboards and reports, using the visualization that I described, that essentially report on the health and the maintenance of the system.

The last is PHP support. It felt to us like an opportunity missed for us not to provide native PHP support. If you’re building a PHP application today and want to use a reporting and analysis tool in an embedded fashion, you have almost no choice. It’s basically a Java world. If I don’t know Java and I know PHP really well, I can now call and use Jaspersoft reporting tools from my PHP program, just like you would if you were a Java programmer before. Everybody’s coding in scripting tools today. If this goes well, you’d likely see us advance that to more of the scripting languages in the future.

Q: Final question: You have 30 seconds with a senior IT executive. Tell them why they should be using Jaspersoft.

A: If you really care about reaching a big percentage of your audience, of your potential business users, with some amount of BI that can be tailored for them, the right place at the right time, and you want to do so affordably, you’re going to need to use Web technologies, you’re going to need to use something that’s purely server-based and that adheres to all these open standards. There’s no other tool on the market today that’s going to do that for you with the affordability and the scalability of Jaspersoft. It’s so compelling to see the environment purely delivered inside a Web browser that immediately what CIOs see is opportunity. When you describe the cost curve, it’s so different than what they’re used to that it spells even more opportunity.

The goal has always been pervasive BI, to get it in front of everybody. The problem is that cost and complexity have prevented that. We think we’ve finally found a formula. What is hard to admit for everyone, is that requires a confluence of technologist and business user. As soon as we overcome that mystery and just admit it, then I think what we’re doing is going to have an enormous impact. There’s no shortcut. It takes technology, it takes business minds. But fundamentally, with the right technology, the right BI platform, the possibilities are remarkably powerful.

This article, “Jaspersoft CEO: We’re driving pervasive business intelligence,” was originally published at InfoWorld.com. Follow the latest developments in business technology news and get a digest of the key stories each day in the InfoWorld Daily newsletter. For the latest developments in business technology news, follow InfoWorld.com on Twitter.