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MicroStrategy, announced version 9.3. The announcement came out of Amsterdam this month just in front of MicroStrategy World, the company’s annual conference for the European market. Release 9.3 delivers significant updates in four main areas: big data, advanced analytics, automated administration and visual data discovery.

The announcements on the big data front have to do with bringing data together from disparate sources, enriching available data, and new report search capabilities. Addressing the need to provide more automated support for data access and preparation are critical as found in our benchmark research on big data and our predictive analytics benchmark research as key obstacles to gaining business value from available data. The data source access improvements in 9.3 include improved access to departmental data, including data from spreadsheets and Salesforce.com, and from multidimensional sources such as Microsoft Analysis Services and Cognos TM1. The software can access data from SAP’s HANA appliance, and use a thrift connector to Hadoop distributions, including those of Cloudera and Amazon Web Services. The data enrichment enhancements include expansion of data based on ZIP code or date. Such location intelligence features address a hot area with great potential in the areas of database cleansing and enrichment. We’ll be exploring these trends in our upcoming benchmark research on location intelligence. MicroStrategy 9.3 also provides a Google-like function to discover reports and a dashboard, so users don’t have to spend unnecessary time looking for reports or creating new ones.

With respect to the Hadoop access, the company has four approaches. The first is to bring data from Hadoop into an in-memory structure for visual exploration and rapid prototyping using the imported data. This approach is interesting, but you still need to define your Hadoop queries before you do the analysis in memory, thus taking away the exploratory element of the big data. The second approach is to do freeform queries directly into Hadoop using Pig Latin or HiveQL.  This approach gives users back the exploratory aspect, but introduces complexity and sacrifices speed. The third approach is to model the data with a traditional multidimensional approach, while the fourth approach is to merge the Hadoop data with the enterprise data warehouse into a uniform view. The company says this last model is gaining traction for a number of their clients, which is in line with what we have been seeing from others in the space. Providing these options are critical as our big data benchmark research found that Hadoop as one of the key technologies planned in almost a third of organizations (32%).

For advanced analytics, the new release integrates R statistical packages into the MicroStrategy BI platform, which allows for advanced in-database analytics with any available R algorithm, including many custom R developments. Version 9.3 supports the most-used algorithms straight out of the box with more than 300 functions. While others have integrated R, few have gone as far as integrating the visualization aspects of R, as MicroStrategy does in this release. R is well-known as an analytical tool, but most users don’t know about its visualization capabilities. The R language is gaining traction in both the academic and business worlds, with universities, large government organizations and the pharmaceutical industry all showing significant support. This integration of predictive analytics into business intelligence is an important step for MicroStrategy and our predictive analytics benchmark found 58 percent of organizations have this as a priority.

The third area of improvement is introduction of System Manager, a GUI administrative workflow tool that the company claims will reduce operating costs by more than 50 percent. The tool allows users to create administrative workflows from both MicroStrategy admin products and third-party tools to do things such as create an Amazon instance. Use cases include MicroStrategy intelligence reports, daily report execution schedules, and migrating objects. The package is priced separately, which is fine since this is a capability most BI packages do not offer.

The fourth and final area of improvement involves the already formidable Visual Insights, a visual data discovery tool MicroStrategy introduced last year. Visual discovery tools continue to gain traction in the market due to their ease of use and their ability to give time back to analysts. Our benchmark research into big data found that visualization is a top priority and unmet need in 37 percent of existing deployments just as is predictive analytics in 41 percent of organizations. The new capabilities of the 9.3 release include density maps, which help to highlight geographic concentration levels such as sales volume. Users can create network diagrams for analytics with web traffic, affinity marketing, or market-basket analysis, and image layouts, which allow for visual mashups. Other enhancements to Visual Insight include a wizard to suggest appropriate visualizations based on the data, the ability to do rank filtering, and shortcuts to commonly used metrics such as counts, moving averages and running totals.  Finally, the ease of creating and distributing dashboards is significantly improved. Drag-and-drop visualizations, and the ability to do visualization-to-visualization overlays, are impressive, and I expect to see others try to emulate these in the future.

Mobile Business Intelligence wasn’t addressed directly in the 9.3 release, but MicroStrategy’s platform for mobile applications was the focus of the 9.2.1m release in January. Mobile intelligence is a big part of the MicroStrategy strategy, and it was also a big part of the conference in Amsterdam. In a separate blog post, I wrote about Michael Saylor’s keynote speech, his new book, The Mobile Wave, and the company’s direction in mobile technology. MicroStrategy has been investing heavily in mobile for a while, especially around native support for Apple’s iOS.

In sum, the MicroStrategy 9.3 release is a big advancement for a firm already providing leadership in the analytics market. Given the firm’s advantage of being an enterprise platform and moving into discovery tools with Visual Insights, it is likely in a better position to expand than many of the discovery players trying to move upstream into an enterprise role. The fact that the company has built the platform from the ground up also gives it an advantage over some of the larger players with less than organic strategies. For organizations with MicroStrategy already installed, the 9.3 upgrade (and memory upgrades) makes plenty of sense. Any firm looking for deeper support of Hadoop, predictive analytics and visual discovery should examine this 9.3 release from MicroStrategy.

Regards,

Tony Cosentino – VP & Research Director

On the heels of the release of his new book, The Mobile Wave, Microstrategy’s CEO Michael Saylor delivered an interesting keynote at Microstrategy World in Amsterdam this past week. Unlike other keynotes we’ve seen at various supplier conferences, the presentation was not a sales pitch. There was no reference to the fact that the company was simultaneously launching MicroStrategy 9.3, a major new release of its flagship offer. The presentation focused almost entirely on the rise of mobile computing and its ability to change the world. Saylor sees the Apple iPad at the heart of the mobile revolution, and notes that BI capabilities delivered through the device are displacing paper and people within organizations. The iPad’s 10-inch screen, which can display 90 percent of printed pages, is the key for companies to unlock the shackles of the physical office environment. Between the lines, it’s easy to read that Microstrategy is betting a lot on mobile and on the iPad.

Saylor’s argument against paper is relatively straightforward. For years we’ve been talking about the paperless office, but technology has not yet allowed us to get away from paper, and executives are still using it for all types of reports and data. Business intelligence before mobile was restricted to columnar reporting, and business intelligence before device interactivity was a manual, paper-based process in which an executive asked an analyst to run a report to answer a question, then looked at the report on paper. The results often inspired other questions, sending the executive back to the analyst to run yet another report – and so on.  Finally, once the executive’s questions were answered, he could ask an employee to take action based on his conclusions.

The iPad, Saylor argues, changes all of this, since iOS and the 10-inch screen allow us to look at standard-size documents and interact with company data. Given the revolutionary capabilities of mobile BI systems, an executive can interactively and visually query multiple data sources, get answers immediately, run his own scenarios, and take action, all from the sidelines of his kid’s soccer game. The executive, now doing the job of three people, is much more productive (if a bit lonelier).

How does the Microstrategy iPad-focused BI strategy stack up in the new mobile world that also contains tablets such as Google’s Nexus 7 and Microsoft’s Surface? With his presentation and over the course of the conference, Saylor took aim at the mobile strategy of a number of industry stalwarts, including Google and Microsoft. Microsoft in particular, he suggested, alienated both its customers and its partners with its recent preannouncement of the Surface tablet computer.

The most obvious competitor currently in the enterprise environment is Google’s Android, but the Android development community is focused around the smartphone, not the tablet. Google’s Nexus 7 suggests that the company is not keen to take on the iPad directly in the enterprise market; the 7-inch screen suggests consumer ambitions. One argument that Saylor gives against the Android is that it lacks tight enough integration between the hardware and the software for delivery on a 10-inch device. I’m curious whether this argument will still hold as Google starts to produce larger form-factor devices with tighter hardware and software integration, and as improved content parsing technologies allow for more information to be consumed on different-sized devices.

The more interesting enterprise play is around Microsoft’s Surface tablet running Windows 8 on Intel chips. When it is finally introduced, the Microsoft advantages will be hard to ignore. As it moves away from ARM-based chips, Microsoft will be able to provide full access to entrenched office productivity software, tight integration with other Windows-based hardware and software, and backward compatibility.  Hewlett Packard, in signing with Intel earlier this year, signaled its own move into Windows 8 tablets. HP’s global distribution power could make this an important milestone. The challenge is whether business will engage and consider Microsoft tablet or how many folks will bring this technology into business and expect support for it with business intelligence.

Unlike Google today and Microsoft tomorrow, Apple takes a “walled garden” approach to its operating system and applications, and enterprise IT departments generally do not like this idea, especially as it relates to security. On the other hand, the developer community in this garden is huge, and the “bring your own device” (BYOD) trend is really helping drive iPhone and iPad into the corporate market. The most influential businesspeople and cultural icons in our society carry iPads, and corporations, much to the chagrin of IT departments all over the world, are being forced to deal with this phenomenon.

On a practical note, I had an opportunity to test-drive MicroStrategy’s platform for mobile applications. I built a number of interactive mobile dashboards for the iPad, the iPhone, and for my own smartphone running Android. While things worked well with the iPad and the iPhone, the Android applications had a lot of issues. I’m not sure if this was due to the lack of Microstrategy focus on Android, or to Android itself. What I do know is that Microstrategy Mobile works well on iPad; just about any user can create designs with minimal training, and not having to wait for coders is a huge advantage.

Nevertheless, an Apple-focused bet in the enterprise environment is a bit risky as new devices come onto the market. It will be interesting to look at Microstrategy’s tack in the context of our upcoming Next Generation Business Intelligence Benchmark Research, which focuses on mobile and collaboration technologies in the enterprise BI environment.

Regards,

Tony Cosentino – VP & Research Director

Actuate, the driving force behind the open source Eclipse Business Intelligence and Reporting Tools (BIRT) project, is positioning itself in the center of the big-data world through multiple partnerships with companies such as Cloudera, Hortonworks, KXEN, Pervasive and a number of OEMs. These agreements, following on its acquisition of Xenos a couple of years ago, help Actuate address some big issues in big data, involving enterprise integration and closed-loop operational systems that provide what my colleague Robert Kugel refers to as action-oriented information technology systems. Today, most initiatives in big data and Hadoop are still in the proof-of-concept stages or being implemented in organizational siloes. Actuate, with its enterprise orientation and federated architecture, is in a position to potentially advance these efforts in a variety of ways.

Actuate’s back-to-back announcements with Cloudera and Hortonworks give support to the 1.5 million BIRT developers and begin to solidify the ties between the BIRT and Hadoop open source communities. Actuate first announced support for Hadoop with the release of BIRT 3.7 last year when it gave BIRT developers access to Hadoop through Hive Query Language (HQL). Hive allows BIRT native access to Hadoop as a data source and provides a single interface for analysis and reporting across a variety of multistructured data sources. These steps answer the finding in our benchmark research on Hadoop and Information Management that users require more efficient methods to access Hadoop HDFS. The overall result of the partnerships is out-of-the-box access for the two leading distributions of Hadoop, enabling organizations to integrate big data more easily into their BIRT environments.

In the analytics and visualization space, Actuate signed agreements with Pervasive and KXEN. RushAnalyzer, Pervasive’s predictive analytics tool that runs natively on Hadoop, will be integrated with the ActuateOne product suite. The combination of Rush Analyzer and ActuateOne gives business users the ability to transform and analyze big data, and puts advanced visualization capabilities in the hands of analysts. The KXEN partnership goes further into predictive analytics by integrating with KXEN’s flagship product, InfiniteInsight. This gives users capabilities in key areas of predictive analytics such as cross-selling and up-selling, churn analytics, next-best-offer and market basket analysis. Our benchmark research in big data finds that predictive analytics is a capability not available in 41 percent of organizations.

Actuate’s OnDemand software is delivered via both PaaS and SaaS. Here Actuate has signed deals with a number of companies, including BMC Software, Cisco, Computer Associates, GE Healthcare, Infor and Siemens, and more recently with Access Data, eMeter and Integrated Data Services. In all, Actuate has more than 200 OEM partnerships, which are of particular importance as companies and developers turn toward the cloud for big-data platform development. Our benchmark research in big data shows that while most current deployments are on-premises, hosted and SaaS deployments will grow faster moving forward.

In addition to the multiple partnerships, Actuate is positioned to ride the big-data wave with Xenos, a content management company it acquired in 2010. Integration with Xenos Enterprise Server allows BIRT developers to design a user front end for powerful parsing technology that enables mining of multistructured data buried in legacy documents and archives of statements, forms and records.

Overall, I see a three-pronged big-data strategy emerging from Actuate. On one front, it offers an enterprise business intelligence system that easily builds reports using any source of data. A large and growing developer community provides the company with the ability to explore all types of relationships and adjust quickly and nimbly to competitors. On the second level, Actuate provides OEM application developers the ability to invoke broad BI functionality within their own custom applications. This will likely prove to be more important as companies move to cloud-based technologies and closed-loop operational intelligence systems that can drive immediate action within a single desktop or mobile interface. In these first two areas, Actuate is at home in terms of its targets in the enterprise, being well-known among enterprise application developers.

It’s on the third front where I think things get interesting for the company, Actuate’s Performance Analytics software, which my colleague Mark Smith wrote about earlier this year. This application focuses on the lines of business and competes with some discovery tools in the market that have already gained traction. Given the shifting landscape of the enterprise buying center with respect to big data, this group is very important as our big data benchmark research has found. The key for Actuate will be to link big data and predictive analytics capabilities that they gain through partner relationships back to its growing business analytics environment operating across the Internet to the mobile environment. If the company can do so, it will position itself well in business environments where analytics need to be pushed out to support real-time and interactive decision-making by front-line managers.

Regards,

Tony Cosentino – VP & Research Director

As volumes of data grow in organizations, so do the number of deployments of Hadoop, and as Hadoop becomes widespread, more organizations demand data analysis, ease of use and visualization of large data sets. In our benchmark research on Hadoop, 88 percent of organizations said analyzing Hadoop data is important, and in our research on business analytics 89 percent said it is important to make it simpler to provide analytics and metrics to all users who need them. As my colleague Mark Smith has noted, Datameer has an ambitious plan to tackle these issues. It aims to provide a single solution in lieu of the common three-step process involving data integration, data warehouse and BI, giving analysts the ability to apply analytics and visualization to find the dynamic “why” behind data rather than just the static “what.”

The Datameer approach places Hadoop at the center of the computing environment rather than looking at it as simply another data source. This, according to company officers, allows Datameer to analyze large, diverse data sets in ways that traditional approaches cannot, which in turn enables end users to answer questions that may have fallen outside of the purview of the standard information architecture. However, Datameer does not offer its software as a replacement for traditional systems but as a complement to them. The company positions its product to analyze interaction data and data relationships to supplement transactional data analysis of which both are key types of big data that need analysis. Of course, given that most companies are not likely to rip and replace years of system investment and user loyalty, this coexistence strategy is a pragmatic one.

Datameer approaches analytics via a spreadsheet environment. This, too, is pragmatic because, as our business analytics benchmark research shows, spreadsheets are the number-one tool used to generate analytics (by 60% of organizations). Datameer provides descriptive analysis and an interactive dialog box for nested joins of large data sets, but the tool moves beyond traditional analysis with its ability to provide analytics for unstructured data. Path and pattern analyses enable discovery of patterns in massive data sets. Relational statistics, including different cluster techniques, allow for data reduction and latent variable groupings. Data parsing technology is a big part of unstructured data analysis, and Datameer provides prebuilt algorithms for social media text analytics and blogs, among other sources. In all, more than 200 prebuilt algorithms come standard in the Datameer tool set. In addition, users can access spreadsheet macros, open APIs to integrate functions and use the Predictive Model Markup Language (PMML) for model exchange.

In Datameer’s latest version 2.0 it has advanced in providing business infographics tool that provides a visualization layer that enables exploratory data analysis (EDA) through a standard library of widgets, including graphs, charts, diagrams, maps and word clouds. Visualization is one of the key areas lacking in big data deployments today. Analysts work in a free-form layout environment with an easy-to-use drag-and-drop paradigm. Datameer’s WYSIWYG editor provides real-time management of the creation and layout of infographics, allowing analysts to see exactly what the end design will look like as they create it. It also now distributes through HTML5, which allows cross-platform delivery to multiple environments. This is particularly important as Datameer is targeting the enterprise environment, and HTML5 provides a low-maintenance “build once, deploy anywhere” model for mobile platforms.

Datameer is an innovative company, but its charter is a big one, given that it is in a competitive environment at multiple levels of the value delivery chain. Its ability to seamlessly integrate analytics and visualization tools on the Hadoop platform is a unique value proposition; at the same time, it will likely need to put more effort into visualization that is available from other data discovery players. All in all, for enterprises looking to take advantage of large-scale data in the near term that don’t want to wait for other vendors to provide integrated tools on top of Hadoop, Datameer is a company to consider.

Regards,

Tony Cosentino – VP & Research Director

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