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I want to share my observations from the recent annual SAS analyst briefing. SAS is a huge software company with a unique culture and a history of success. Being privately held SAS is  not required to make the same financial disclosures as publicly held organizations, it released enough information to suggest another successful year, with more than $2.7 billion in revenue and 10 percent growth in its core analytics and data management businesses. Smaller segments showed even higher growth rates. With only selective information disclosed, it’s hard to dissect the numbers to spot specific areas of weakness, but the top-line figures suggest SAS is in good health.

One of the impressive figures SAS chooses to disclose is its investment in research and development, which at 24 percent of total revenue is a significant amount. Based on presentations at the analyst event, it appears a large amount of this investment is being directed toward big data and cloud computing. At last year’s event SAS unveiled plans for big data, and much of the focus at this year’s event was on the company’s current capabilities, which consist of high-performance computing and analytics.

SAS has three ways of processing and managing large amounts of data. Its high-performance computing (HPC) capabilities are effectively a massively parallel processing (MPP) database, albeit with rich analytic functionality. The main benefit of HPC is scalability; it allows processing of large data sets.

A variation on the HPC configuration includes pushing down operations into third-party databases for “in-database” analytics. Currently, in-database capabilities are available from Teradata and EMC Greenplum, plus SAS has announced plans to integrate with other database technologies. The main benefit of in-database processing is that it minimizes the need to move data out of the database and into the SAS application, which saves time and effort.

More recently, SAS introduced a third alternative that it calls High Performance Analytics (HPA), which provides in-memory processing and can be used with either configuration. The main benefit of in-memory processing is enhanced performance.

These different configurations each have advantages and disadvantages, but having multiple alternatives can create confusion about which one to use. As a general rule of thumb, if your analysis involves a relatively small amount of data, perhaps as much as a couple of gigabytes, you can run HPA on a single node. If your system involves larger amounts of data coming from a database on multiple nodes, you will want to install HPA on each node to be able to process the information more quickly and handle internode transfers of data.

SAS also has the ability to work with data in Hadoop. Users can access information in Hadoop via Hive to interact with tables as if they were native SAS data sets. The analytic processing is done in SAS, but this approach eliminates the need to extract the data from Hadoop and put it into SAS. Users can also invoke MapReduce jobs in Hadoop from the SAS environment. To be clear, SAS does  not automatically generate these jobs or assist users in creating them, but this does offer a way for SAS users to create a single process that mixes SAS and Hadoop processing.

I’d like to see SAS push down more processing into the Hadoop environment and make more of the Hadoop processing automatic. SAS plans to introduce a new capability later in the year called LASR Analytic Server that is supposed to deliver better integration with Hadoop as well as better integration with the other distributed databases SAS supports, such as EMC Greenplum and Teradata.

There were some other items to note at the event. One is a new product for end-user interactive data visualization called Visual Analytics Explorer, which is scheduled to be introduced during the first quarter of this year. For years SAS was known for having powerful analytics but lackluster user interfaces, so this came as a bit of a surprise, but the initial impression shared by many in attendance was that SAS has done a good job on the design of the user interface for this product.

In the analytics software market, many vendors have introduced products recently that provide interactive visualization. Companies such as QlikViewTableau and Tibco Spotfire have built their businesses around interactive visualization and data exploration. Within the last year, IBM introduced Cognos Insight, MicroStrategy introduced Visual Insight, and Oracle introduced visualization capabilities in its Exalytics appliance. SAS customers will soon have the option of using an integrated product rather than a third-party product for these visualization capabilities.

Based on SAS CTO Keith Collins’s presentation I expect to see SAS making a big investment in SaaS (software as a service, pun intended) and other cloud offerings, including platform as a service and infrastructure as a service. Collins outlined the company’s OnCloud initiative, which begins with offering some applications on demand and will roll out additional capabilities over the next two years. SAS plans full cloud support for its products, including a self-service subscription portal, developer capabilities and a marketplace for SAS and third-party cloud-based applications and also plans to support public cloud, private cloud and hybrid configurations. Since SAS already offers its products on a subscription basis, the transition to a SaaS offering should be relatively easy from a financial perspective. This move is consistent with the market trends identified in our Business Data in the Cloud benchmark research. We also see other business intelligence vendors such as MicroStrategy and information management vendors such as Informatica adopting similarly broad commitments to cloud-based versions of their products.

Overall, SAS continues to execute well. Its customers should welcome these new developments, particularly the interactive visualization. The big-data strategy is still too SAS-centric, focused primarily on extracting information from Hadoop and other databases. I expect that the upcoming LASR Analytics Server will leverage these underlying MPP environments better. The cloud offerings will make it easier for new customers to evaluate the SAS products. I recommend you keep an eye on these developments at they come to market.

Regards,

David Menninger – VP & Research Director

MicroStrategy, one of the largest independent vendors of business intelligence (BI) software, recently held its annual user conference, which I attended with some of my colleagues and more than 2,000 other attendees. At this year’s event, the company emphasized four key themes: mobility, cloud computing, big data and social media. In this post, I’ll assess what MicroStrategy is doing in each of the first three areas. My colleague, Mark Smith, covered MicroStrategy’s social intelligence efforts in his blog. I’ll also share some opinions on what might be missing from the company’s vision.

Michael Saylor, MicroStrategy’s CEO, is enamored with Apple and its mobile technology, which sure seems to be a good bet. Coincidentally, on the same day Saylor delivered his keynote speech, Apple announced record revenues based on iPhone and iPad sales. MicroStrategy made an early commitment to mobile technologies and Apple’s products. As a result it has a relatively mature set of native mobile products on the Apple platform; now it is bringing those capabilities to Android devices via the Android Marketplace. In addition to Android platform support, the current release, 9.2.1m, adds new mobile features including offline capabilities and user interface enhancements. As a testament to the maturity of MicroStrategy’s mobile capabilities, several customers I spoke with were deploying mobile applications first and then extending those applications to Web and desktop platforms.

At last year’s MicroStrategy World, the company was just getting familiar with the cloud. Since then it has delivered two types of cloud capabilities: Cloud Personal for individual use and a cloud version of its full platform including database and data integration capabilities. Support for Teradata in the enterprise cloud offering extends previously announced support for IBM Netezza and ParAccel. Data integration capabilities are provided via a partnership with Informatica. At the recent event it also introduced a third version (not yet available): Cloud Professional extends Cloud Personal with multiuser capabilities including user management, security, personalization and notification of dashboard updates. In addition, Cloud Personal has added the ability to import data directly from Salesforce.com applications.

It’s still early days for MicroStrategy in the cloud, as it is for most vendors, but the company appears to be “all in.” It has committed $100 million dollars to build out the cloud infrastructure and offers free capabilities to individual users via Cloud Personal. Perhaps most significant are the software partnerships to provide database and data integration capabilities – the first revenue sharing partnerships for MicroStrategy. In the past it delivered only capabilities developed internally. It made no acquisitions and no partnerships. This willingness to share revenue demonstrates how important the cloud is to MicroStrategy.

The company chose to be practical rather purist in its approach. The cloud implementation is based on MicroStrategy’s existing product architecture which is not multitenant. In other words each enterprise runs in a separate instance of the software rather than sharing a single instance. This approach has no immediate or obvious downside for customers. However, in the long run, it could prove to be more expensive and labor-intensive for MicroStrategy. Company officials said that over time it will migrate to a multitenant architecture to overcome these issues.

Another key theme, big data, received less attention. Certainly, MicroStrategy executives and presenters mentioned big data, but that is not new to the company. MicroStrategy built its business around large data sets, often from the retail industry, before the concept of “big data” existed. As a result, its core BI product has been architected to deal with big data which is evidenced by its longstanding relationship with Teradata and some of the other databases it supports, including Greenplum, Netezza, ParAccel and Vertica. In addition, MicroStrategy and Cloudera recently announced a partnership that  provides connectivity to Hadoop data sources. As our benchmark research shows, organizations use multiple technologies to tackle big-data challenges so MicroStrategy customers should welcome this partnership.

I see a couple of holes in MicroStrategy’s coverage. Mark Smith discusses how MicroStrategy is tackling social media as a data source. However, the company has not embraced social media in the context of collaborative BI. In a recent blog post, I noted that Ventana Research sees collaboration as one of five key influences on business intelligence, and there is plenty of movement here. Enterprises have started to adopt collaborative BI processes. Other BI software vendors have begun to support collaborative BI in their products. Soon we’ll be researching market requirements in an upcoming benchmark research project. Another area where MicroStrategy lags some of its competitors is advanced analytics. The company has some support for predictive analytics but limited capabilities for planning and what-if analysis.

Despite these areas where MicroStrategy can make additional investments, its annual event demonstrated the company’s determination to embrace new technologies and expand the horizons of business intelligence. It was well attended by customers and supported by a range of partners. If you are struggling with big data, mobile or cloud challenges, you may want to consider MicroStrategy. If so, you can try it easily via its cloud offerings.

Regards,

David Menninger – VP & Research Director

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