Last week, I provided an overview of Gartner’s data warehouse Magic Quadrant (DW MQ). I explained that the DW MQ has a lot of significance for the Big Data world. The same is true of the Business Intelligence Magic quadrant (BI MQ) which was released just five days later. As such, I thought it a good idea to let the DW MQ analysis sink in and then provide a similar summary for the BI MQ this week.
The BI MQ has many more vendors than does the DW MQ (with all of last year’s vendors retained and three new ones added to this year’s MQ), and so I’m not going to each vendor included in the report. As before, I will recommend you read the full report in any case, and will instead concentrate on some of the trends and themes that evidenced themselves in the report that were not explicitly spelled out.
A BI Vendor Primer
Before covering those trends, though, some background on the BI vendor lineup may be in order.
One thing to keep in mind as you consider both the BI MQ and DW MQ reports, is that the “MISO” vendors (Microsoft, IBM, SAP and Oracle) figure prominently in both. There are major pure plays on the BI MQ side, too: just as Teradata is a specialist vendor in the DW space, but a substantial force nonetheless, so too are a certain vendors in the BI world, including SAS and MicroStrategy.
BI has more subcategories than does the DW space. One of them – involving interactive visualization for data exploration and discovery, has crowned its own kings: Tableau is chief among them, QlikTech’s QlikView is right behind it and Tibco’s Spotfire is there too.
The Big Data world is dominated by Open Source technologies; the BI world, not so much. But there are Open Source BI players, and three of them — Pentaho, Jaspersoft and Actuate — make a significant showing in this year’s BI MQ.
And speaking of the Big Data world, you will see in the BI MQ report, as you did in the DW MQ, that partnerships and connectors to major Hadoop distributions, and the beginnings of standardization on the R programming language for statistics and predictive analytics, is starting to take place.
In fact, in the near future, we may find that distinguishing between DW, BI and Big Data markets will be a contrived endeavor. These worlds will likely become like neighborhoods in the same city, even if today they seem like loosely federated states. The very reason this blog is called Big onData (and not just “Big Data”) is in anticipation of such unification.
I’ll get down off my soapbox now though. Let’s run through the trends evident in this year’s report.
Microsoft leads in ability to execute
As I did with the DW report, I’ll start with the “winners” in this MQ. Each axis (“ability to execute” and “completeness of vision”) had its own winner, and that for the former is Microsoft. I tend to go out of my way to point out my bias on Microsoft. I built much of my career around Microsoft technologies, especially its developer and BI stacks, and I served on the company’s BI Partner Advisory Council for several years. I’ve long thought the MS BI stack provided significant value, and have watched that value increase recently with the introduction of PowerPivot and SQL Server Analysis Services Tabular mode (in-memory column store databases that are highly integrated with Excel and SharePoint) and Power View (interactive visualization technology integrated with those same products). Microsoft has also recently added Master Data Management and Data Quality tools that, while still maturing, round out very nicely a stack that costs little to nothing for customers already using SQL Server, Office and SharePoint.
So it’s interesting to see strong recognition from Gartner this year of the Microsoft BI stack. Couple that with the Microsoft’s rise on both axes in the DW MQ report, and the impending release of its HDInsight Hadoop distribution for Windows Server and the Windows Azure cloud platform, and I think we’re at a point where everyone needs to pay attention. Again, I am far from objective on this point, but even those that are objective have to take notice.
Meanwhile, Microsoft continues as a laggard in the mobile BI space. While it is technically possible to work with Power View on a Windows 8 tablet, this is not the case for iOS, Android, or even Microsoft’s own Windows RT platform. Power View is still based on Silverlight, which is a technology all but disowned by Redmond, supported only on the full Windows desktop and MacOS (but, again, not iOS) platforms. Microsoft is out of excuses on this one, and it’s no wonder that the company did not win on the MQ’s completeness of vision axis. Which brings us to the company that did.
IBM leads in completeness of vision
IBM, if nothing else, is a master of acquisitions. While it’s long had its DB2 database, and some BI enhancements surrounding it, the company’s acquisition of Cognos (and thus TM1) and SPSS, as well as acquisitions in the analytics space like Netezza and Vivisimo; and even marketing technology acquisitions Unica and Coremetrics, are what have really propelled IBM in the BI space. With so many products in its portfolio, and with subsequent organic additions, like Cognos Insight, Cognos Express and InfoSphere Streams (a complex event processing engine), it seems almost a no-brainer to award IBM the winner in the completeness of vision axis.
- Also read: IBM’s Big Data Analytics Empire
- Also read: NYC Data Week, Day 1: IBM, Tervela, Cisco and SiSense announce
- Also read: IBM eyes vertical applications for big data
Almost three years ago now I gave a talk at Microsoft’s BI conference, presenting a competitive analysis of Microsoft BI in the marketplace. I urged the audience not to underestimate the then-nascent open source BI scene, insisting it would emerge to be an important force in the industry. The two biggest vendors in that space, Pentaho and Jaspersoft, are in the very center of the Niche Players quadrant this year. And Actuate, the company behind open source reporting component BIRT, entered the MQ for the first time, and in the Challengers Quadrant to boot. Another open source BI vendor, SpagoBI, while not included in the MQ, is nonetheless mentioned in the “Other Vendors to Consider” section of the report.
Two things about Pentaho and Jaspersoft are important to keep in mind: they both derive significant revenue from OEMs that embed their technology, and each one is focusing very heavily on connecting to Hadoop and NoSQL data sources. This distinguishes both companies from many of the other vendors in this report (Tableau is an important exception, though) and points out why industry watchers should continue to monitor both companies. Actuate, meanwhile, in acquiring analytics provider Quiterian earlier this year, is working hard to complement its BIRT-based reporting chops with serious data mining, social media analytics and predictive analytics capabilities as well.
The open source guys are playing to win and are successfully using the open source mechanism as a viral marketing tool. These companies are not in this for philanthropy, knowing full well that most of their serious customers will end up acquiring their fee-based enterprise editions, rather than sticking with the open source community editions
MISO vendors each lag, somewhere
The MISO vendors continue to dominate, mostly through achieving status as the corporate BI standard within their customers’ organizations. These vendors have very broad BI stacks (in all cases but Microsoft’s, due largely to acquisitions) and present formidable barriers of entry to their competitors. Even to players like MicroStrategy, SAS and Informtion Builders, the MISOs are still tough to beat, since their stacks (and enterprise licenses) span beyond BI itself.
But Gartner’s BI MQ report this year points out that the MISOs are each lacking in at least one key area. For example, Microsoft and Oracle each lags in mobile, Oracle also lags in interactive visualization, IBM lags in performance and ease of use and SAP lags in integration of its SAP BW and Business Objects stack components and the stability of those components.
In short, each of the MISO megavendors is vulnerable to disruption from the various smaller players, who have the luxury of less legacy code, fewer codebases (due to fewer, if any, acquisitions) and greater concentration on newer BI market imperatives including Big Data, mobile and cloud.
Incumbent pure plays vulnerable
Just as the MISOs are at once dominant and vulnerable, so too are the incumbent pure plays (though less so). Customers report SAS is hard to use and expensive. With open source R coming on as a challenger in the stats/predictive analytics area, the price premium becomes harder still to justify and perpetuate.
Gartner’s research finds that customers find MicroStrategy has a steep learning curve, high licensing and implementation costs, and comes up short on predictive, and what Garter calls “prescriptive,” analytics. Nevertheless, MicroStrategy’s integration of R in its newest version could well mitigate this last shortcoming. Further more, its integration with SAP HANA and Hadoop (via Hive) put it close to the leading edge of BI-Big Data convergence.
Tableau ranks high
Visuald Data discovery player Tableau has entered the BI MQ Leaders Quadrant for the first time this year. The company and its eponymous product achieved among the highest rankings in product quality-related measures, latest release migration, dataset sizes, analytical complexity, analysis of unstructured data, ease of use for developers and end-users, shortest time to implementation, fastest report and dashboard development times, percentage of business user authors and percentage of customers using or targeting cloud deployments in next 12 months.
- Also read: Tableau 8 unveiled. Can it keep the good times rolling?
- Also read: Deloitte unit adopts Tableau as its go-to analytics tool
Data exploration pure plays on back foot
Tableau, QlikTech and Tibco Spotfire face new competition as Enterprise BI vendors add visual exploration to their stacks. Notable also is that all three products offer direct connect options for back end data sources, scaling past their proprietary engines’ capabilities. In the past, only Tableau offered this ability, providing it with a competitive advantage that now seems likely to erode over time, as Qlik and Spotfire’s comparable capabilities help them achieve parity in the marketplace.
All three companies have in recent years upstaged the bigger players with compelling visualizations and, at least in the cases of Tableau and QlikView, tools that business users actually find fun to use. This has given these companies much-deserved traction. But they cannot ignore more enterprise-y features like data integration/extract transform and load (DI and ETL), master data management (MDM) and data quality (DQ) forever, especially when the players that do offer those capabilities are closing the gap on usability and compelling visualizations.
The cloud is coming
Two of the three BI MQ newcomers, Birst and GoodData (the third is Permformance Management provider Bitam), are cloud-based BI vendors. Moreover, open source BI players Pentaho and Jaspersoft pursue cloud-based offerings of their own platforms with gusto. Tableau has Tableau Public. IBM supports Cognos BI 10 in the cloud. And MicroStrategy, SAP, Panorama, Tibco Spotfire, Alteryx and others have cloud options as well.
It should be noted that some cloud-based companies (Gartner mentions Birst explicitly) are achieving traction by offering an on-premise appliance solution as well. For some customers, the road to the cloud is through the corporate data center, however counterintuitive that may seem. When you consider that the real attraction of cloud BI isn’t the off-premise aspect per se, but rather the ease of provisioning, then the appliance option starts to make more sense.
Whatever the approach, it’s clear that a big barrier to BI implementations has been the complexity of installation, configuration and optimization. The more devices available to eliminate that barrier, the better.
Big Data is…big
Many of the BI MQ vendors (at least eight by my count, and likely a lot more) offer integration with Hadoop, and various others offer integration with R, and leading NoSQL databases. So to end near where we began, I’ll once again point out that these worlds are colliding. Part of what will make Big Data enterprise-ready is that the major technologies within it will have the BI capabilities (either natively or through partnerships and integrations) that enterprise customers now rely upon.
There are important companies in this space (SiSense and Datameer come to mind right away) that are not included in the BI MQ. I hope that next year some combination of their revenue and Gartner’s criteria change, so that they are included. Meanwhile, the BI MQ report represents work by Gartner analysts Kurt Schlegel, Rita L. Sallam, Daniel Yuen and Joao Tapadinhas that is nonetheless quite exhaustive.