MicroStrategy Reveals New Generation of Analytics for Cloud and Mobile Computing

At its recent MicroStrategy World 2014 conference, the enterprise software company introduced a portfolio of products to make it easier to perform analytics and make them easier to access throughVRLogobug400x400 the cloud and mobile forms of computing. These announcements accelerate MicroStrategy’s transition to approaching corporate business users of analytics from its past focus on business intelligence, which typically is purchased by IT. This is a subtle but strategic shift that recognizes where growth opportunities lie and that analytics must be available on any device at any time. MicroStrategy made it clear that advances in the cloud, mobility and big data were integral to its product releases last year and is continuing in this direction in 2014 with the products in its MicroStrategy 9.4 suite.

A little recap from the end of 2013 will illustrate the trend. MicroStrategy launched a product called Analytics Desktop that is freely available to download and use. The product runs locally and provides capabilities for data and visual discovery, the building of dashboards and standard business intelligence. This is part of an update to MicroStrategy Analytics Enterprise and also runs in the cloud to support MicroStrategy Analytics Express for self-service analytics. MicroStrategy Analytics Desktop and Analytics Express generate a local data file that securely contains the data and related information for analysis and presentation. This new MicroStrategy file format can be used to import data to both the cloud and on-premises applications. MicroStrategy emphasizes its advantages in analyzing a range of databases and secure Web and mobile publishing, which are freely available in its products while competitors charge for them. In the past some customers and observers perceived MicroStrategy as making it difficult to try out its technology without having to deal with its sales team; now anyone can try it at any time and use it afterward.

At the conference MicroStrategy unveiled release 9.4.1 of its platform, in which ESRI Maps is embedded. It supports a range of vr_LA_most_important_location_analytics_capabilitieslocation analytics, which our research shows is important to three out of four organizations. This capability can be a competitive differentiator for MicroStrategy that other BI providers lack. MicroStrategy 9.4.1 provides location analytics capabilities most important to organizations according to our location analytics benchmark research.

In addition new advances in data blending will appeal to analysts; our information optimization benchmark research finds nearly half (45%) of organizations still spend more of their time on data-related tasks than analysis and recommendations. And there are advances in the platform’s computing power: Now it can handle 10 times more data in memory and has a 40 times performance gain in multisource analytics. MicroStrategy has significant depth in its analytics capability from historical to predictive that most do not realize is more sophisticated than many others in the analytics and BI software market.

Other advances enhance the data performance and scalability of the platform. MicroStrategy Parallel Relational In-Memory Engine (PRIME) is a re-engineering of its OLAP Services and can handle in-memory computing on a massive scale. It has a load rate of more than 7 terabytes per hour and does not require a star schema; clearly this is designed for big data analytics. The CIO of Facebook, Tim Campos, took the stage at MicroStrategy World to discuss his company’s use of PRIME and testified that it can analyze the large volumes of data from activity of Facebook’s billion members. Through PRIME and broader support for big data sources MicroStrategy is able to provide big data analytics that can exploit the span of sources including Hadoop, in-memory processing, appliances, non-SQL data, columnar databases and RDBMSs. MicroStrategy has made significant investments to support any source of data including the very long list of new ones in the big data and noSQL environments such as Cloudera, Hortonworks, MapR, MarkLogic, mongoDB and many others. I was impressed by how widely the company has expanded in embracing these sources. MicroStrategy also has been certified to access data from SAP HANA, which has a rapidly growing ecosystem. MicroStrategy should continue to market into the big data ecosystems, each of which has its own community.

In mobile technology MicroStrategy made a series of announcements for new products now available. For example, MicroStrategy Analytics App for iPad furthers its ability to provide best-in-class mobile capabilities as does the self-service application MicroStrategy Analytics Express for iPad. Both are available in the Apple App Store, where you can download and try them. Probably more important is significant improvement to the computing experience of MicroStrategy’s native support for Apple iOS 7; it also supports transactional computing through widgets in the application. MicroStrategy Usher offers full support for identity management and secure access to applications, making this one of the most secure platforms for analytics and applications. MicroStrategy also will make technical support available on mobile platforms in an application coming soon through iTunes App Store.

Our analysis of business intelligence for mobile technology confirms VRMobileBIVI_HotVendorMicroStrategy’s leading position in this market. Our recently released 2014 Value Index on Mobile Business Intelligence rates MicroStrategy the top Hot vendor among the 16 we assessed. Mobile capabilities for using business intelligence are important to 69 percent of organizations according to our next-generation business intelligence research. Operating on Apple and Android devices while supporting Web browser-based support for Microsoft Surface devices puts MicroStrategy in position to gain a return from its mobile investments.

In cloud computing, MicroStrategy ranks highly in adoption by very large corporations. But many organizations do not know much about its cloud offering compared to its on-premises and mobile approaches. Yet this is increasingly important: Our research finds in enterprise business intelligence 47 percent of organizations prefer on-demand access or applications hosted by the supplier. MicroStrategy needs to make its cloud presence known, and PRIME for large scale in-memory computing will be available exclusively in the cloud, which should highlight its efforts. To be more successful with its cloud offering the company will need to focus on the lines of business: sales, marketing, human resources, customer service, finance and others where cloud computing has advanced rapidly where business has used its operational expense budget to acquire applications and tools on the Internet.

At MicroStrategy World a variety of speakers from customer companies discussed not only what they are doing in analytics and business intelligence but also how mobile technology is enabling a new class of applications for internal use and in relating directly to consumers; examples were fashion retailer GUESS and Gucci, which demonstrated its new mobile application for customer engagement. Also present was the CIO of McCain Foods, Roman Coba, who was the recipient of our 2011 CIO Leadership Award. The many presenters showed MicroStrategy does not lack customer validation of the use of its tools.

For enterprise management of its technology the MicroStrategy Health Center continues to advance in diagnosing problems and suggesting fixes. Through diagnostics and alerts from the center, administrators can take action to resolve issues. For those serious about enterprise deployment of analytics for business and business intelligence in IT, this approach to support is essential.

vr_Info_Optimization_02_drivers_for_deploying_informationIn addition, MicroStrategy is advancing in information optimization, which is about providing relevant and timely information to business users on any device at any time. Our research on the topic finds that analytics is the top driver in two-thirds of organizations and that information access in general is critical to more than half. Also MicroStrategy’s investments in Usher for identity management and applications like Alert are critical for interactions with customers; our latest customer engagement research finds that mobility and analytics are the top technologies companies will apply to this business priority.

MicroStrategy is off to a great start this year with a solid portfolio of products and has made strong progress since my colleague Tony Cosentino analyzed its efforts. To realize its potential the company will have to market the portfolio of possibilities better, as the products are ready to help organizations. The only area that it has not invested is providing online collaboration among business users and analysts to streamline analytics and business processes and reduce the encumbrances of email and meetings.  Generating more awareness on its support for discovery and exploration across big data both visually and interactively on data will help it grow even faster to meet the demand for analytics by business. If you have not examined MicroStrategy lately, try out its free products for cloud, mobile and Web environments.


Mark Smith

CEO & Chief Research Officer

Teradata Brings In-Memory Computing and Data Discovery to Big Data

Teradata recently gave me a technology update and a peek into the future of its portfolio for big data, information management and business analytics at its annual technology influencer summit. The company continues to innovate and build upon its Teradata 14 releases and its new processing technology. Since my last analysis vr_bigdata_big_data_technologies_plannedof Teradata’s big data strategy, it has embraced technologies like Hadoop with its Teradata Aster Appliance, which won our 2012 Technology Innovation Award in Big Data. Teradata is steadily extending beyond providing just big data technology to offer a range of analytic options and appliances through advances in Teradata Aster and its overall data and analytic architectures. One example is its data warehouse appliance business, which according to our benchmark research is one of the key technological approaches to big data; as well Teradata has advanced support with its own technology offering for in-memory databases, specialized databases and Hadoop in one integrated architecture. It is taking an enterprise management approach to these technologies through Teradata Viewpoint, which helps monitor and manage systems and support a more distributed computing architecture.

By expanding its platform to include workload-based appliances that can support terabytes to petabytes of data, its Unified Data Architecture (UDA) can meet a broad class of enterprise needs. That can help support a range of big data analytic needs, as my colleague Tony Cosentino has pointed out, by providing a common approach to getting data from Hadoop into Teradata Aster and then into Teradata’s analytics. This UDA can begin to address challenges in data activities and tasks in the analytic process, which our research finds are issues for 42 percent of organizations. Teradata Aster Big Analytics Appliance is for organizations that are serious about retaining and analyzing more data, which 29 percent of organizations in our research cited as the top benefit of big data technology. This appliance can handle up to 5 petabytes and is tightly integrated with Aster and Hadoop technology from Hortonworks, a company that is rapidly expanding its footprint, as I have already assessed.

The packaged approach of an appliance can help organization address what our technology innovation research identified as the largest challenges in big data: not enough skilled resources (for 56% of organizations) and being hard to build and maintain (52%). These can be overcome if an organization designs a big data strategy that can apply a common set of skills, and the Teradata technology portfolio can help with that.

At the influencer summit, I was surprised that Teradata did not go into the role of data integration processes and the steps to profile, cleanse, master, synchronize and even migrate data (which its closest partner, Informatica, emphasizes) but focused more on access to and movement of data through its own connectors, Unity Data Mover, Smart Loader for Hadoop and support of SQL-H. For most of its deployments there is a range of complementary data integration technology from its partners as much as it is a Teradata only approach. For SQL-H Teradata takes advantage of the metadata HCatalog to improve access to data in HDFS. I like how Teradata Studio 14 helps simplify the view and use of data in Hadoop, Teradata Aster and even spreadsheets and flat files for building sandbox and test environments for big data. (To learn more, look into the Teradata Developer Exchange.) Teradata has made it easy to add connecters to get access to Hadoop on its Exchange which is a great way to get the latest advances in its utilities and add-ons to its offerings.

Teradata provided an early peak on the just announced Teradata Intelligent Memory, a significant step in adapting big data architectures to the next generation of memory management. This new advancement can cache and pool data that is in high demand (hot) across any number of Teradata workload-specific platforms by processing data to determine the importance of data (described as hot, warm or cold) for fast and efficient access and applying analytics. This technological feat can then utilize both solid-state and conventional disk storage to ensure the fastest access and computation of the data for a range of needs. This is a unique and powerful way to support an extended memory space for big data and to intelligently adapt to the data patterns of user organizations; its algorithms can interoperate across Teradata’s family of appliances.

Teradata has also invested further into its data and computing architecture through what it calls fabric-based computing. That can help connect nodes across systems through access on the company’s Fabric Switch using its BYNET, Infiniband and other methods. (Teradata participates in the OpenFabrics Alliance, which works to optimize access and interconnection of systems data across storage-area networks.) Fabric Switch provides an access point through which other aspects of Teradata’s UDA can access and use data for various purposes, including backup and restore or data movement. These advances will significantly increase the throughput and combined reliability of systems and enhance performance and scalability at both the user and data levels.

Tony Cosentino pointed out the various types of analytics that Teradata can support; one of them is analytics for discovery through its recently launched Teradata Aster Discovery Platform. This directly addresses two of the four types of discovery I have just outlined : data and visual discovery. Teradata Aster has a powerful library of analytics such as path, text, statistical, cluster and other areas as core elements of its platform. Its nPath analytic expression has significant potential in enabling Aster to process distributed sets of vr_bigdata_obstacles_to_big_data_analyticsdata from Teradata and Hadoop in one platform. Analytic architectures should apply the same computational analytics across systems, from core database technology to Teradata Aster to the analytics tools that an analyst is actually using. Aster’s approach to visual and data discovery is challenging in that it requires a high level of expertise in SQL to make customizations; the majority of analysts that could use this technology don’t have that level of knowledge. But here Teradata can turn to partners such as MicroStrategy and Tableau, which have built more integrated support for Teradata Aster and offer easier to use that are interactive and visual designed for analysts who do not want to muck with SQL. Teradata has internal challenges in improving support for analysts and the analytic processes they are responsible for; its IT-focused, data-centric approach will not help here. Our big data research finds that staffing and training are the top two barriers for using this technology, according to more than 77 percent of organizations; vendors should note this and reduce the custom and manual work that requires specific SQL and data skills in their products.

Regarding analytics specifically, Teradata has continued to deepen its analytics efforts with partner SAS. A new release of Teradata Appliance supports SAS High-Performance Analytics VR_leadershipwinnerfor up to 52 terabytes of data and also supports SAS Visual Analytics, which I have tried and assessed and tried myself.

Through its Teradata Aprimo applications Teradata continues its efforts to attract marketing executives in business-to-consumer companies that require big data technology to utilize a broad range of information. Teradata has outlined a larger role for the CMO with big data and analytics capabilities that go well beyond its marketing automation software. The company announced expansion to support predictive analytics and has outlined its direction for supporting customer engagement. It needs to take steps such as these to ensure it tunes into business needs beyond what CIOs and IT are doing with Teradata as a big data environment for the enterprise.

Along these lines I have also pointed out that we should be cautious about accepting research that predicts the CMO will outspend the vr_CRM11_Inbound_InteractionsCIO in the future. What I have seen in these assertions is flawed in many facets and often come from those who have no experience in market research and the role marketing and dealing with technology expenditure in that context. As we have done research into both the business and IT sides, we have discovered the complexities of making practical technology investments; for example, our research into customer relationship maturity found that inbound interactions from customers occur across many departments; they occur in marketing (in 46% of organizations), but more often through contact centers (77%), where Teradata should strengthen its efforts. On the plus side Teradata continues to demonstrate success in assisting customers in marketing, winning our 2013 Leadership Award for Marketing Excellence with its deployment at International Speedway Corp. and in 2012 at Nationwide Insurance with Teradata Aprimo. Our current research into next-generation customer engagement already identifies a need to support multichannel and multidepartment interactions. Teradata could further expand its efforts in these areas with existing customers; KPN won our 2013 Leadership Award in Customer Excellence after connecting Teradata with its Oracle-based applications and supporting BI systems.

Overall Teradata is doing a great job of focusing on its strengths in big data and areas where it can maximize the impact of its analytics, especially marketing and customer relations. While IBM, Oracle, SAP and other large technology providers in the database and analytic markets tend to minimize what Teradata has created, it is has a loyal customer base that is attracted to the expanded architectures of its appliances and its broader UDA and intelligent memory systems. I think with more focus on the processes of real business analysts and further simplifying usability, Teradata’s opportunity could grow significantly. In helping its customers process more of the vast volumes of data and information from the Internet, such as weather, demographic and social media,  it could make clear the broader value of big data in optimizing information  from the variety of data in content and documents. It could expand its new generation of tools and applications to exploit the use of this information as it is beginning to do with marketing applications from Teradata Aprimo. If Teradata customers find it easier to access information and share it across lines of business through social collaboration and mobile technology, that will further demand for its technology to operate on larger scales in both the number of users and the places where it can be accessed even via cloud computing. Exploiting in-memory computing along with providing more discovery potential from analytics will help its customers utilize the power of big data and trust in Teradata to supply it.


Mark Smith

CEO & Chief Research Officer