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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 
of 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 
data 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 
for 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 
CIO 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.
Regards,
Mark Smith
CEO & Chief Research Officer
I recently attended the annual SAS analyst summit to hear the latest 
company, product and customer growth news from the multi-billion-dollar analytics software provider. This global giant continues to grow its business and solutions to help with fraud prevention, marketing and risk. It lets users apply its analytic and statistical technology in practical applications for business. SAS can meet midsized businesses’ demand with packaging and pricing to ensure it is not seen as only affordable to Global 2000 companies. SAS’ growth in analytics should be no surprise, as our research finds analytics to be the first-ranked priority among technologies for innovating business.
SAS’ largest area of growth is in its business analytics and business intelligence tools. Its new SAS Visual Analytics product appeals to a 
broad range of business and analyst needs. The latest upcoming version blends data and visual discovery with powerful analytics. SAS is also addressing usability, the most important technology consideration according to 63 percent of organizations in our research. SAS uses in-memory computing against big data to help meet the advanced needs of organizations. Its eventual intent is to have Visual Analytics be the focal point of its business intelligence product direction. SAS Visual Analytics 6.2 is expected to be generally available in second quarter of this year; a trial of the product is already available. At the event the company demonstrated its capabilities on tablets such as the Apple iPad. After seeing the demo my only recommendation is that SAS provide more collaborative aspects and ensure that analysts can make observations and notations, which is a challenge with most of the business intelligence and analytics offerings in the market today.
SAS’ view of big data echoes our view that it is part of a larger portfolio of 
business technology for storing and loading data. SAS has invested significantly into its high performance analytics (HPA) architecture, which enables it to operate in parallel or embedded within database technology. SAS has focused on efficient processing for applying mathematics, and has devised multiple architectural approaches to adapt to existing technology, including Hadoop, and to ensure it can operate in the most efficient manner. Our big data research finds that a third of organizations plan to evaluate and adopt a range of appliances, in-memory and specialized databases and Hadoop in 2013. SAS’ approach is to embrace and integrate with a range of big data approaches.
For information management, SAS has consolidated the previous Dataflux brand into the SAS organization and unified its product 
offerings. This is an important move, as joint offerings can confuse potential customers, though everything was available from SAS. Beneath the marketing is a solid product line that provides not just data integration, though we assessed SAS as a Hot Vendor in our 2012 Value Index for Data Integration based on a methodical assessment. Unlike other analyst approaches that scratch the surface of review in 2×2 assessments, we look at range of manageability, usability, reliability and other categories that span a range of data related areas. Not as well-known yet for its integration with Hadoop and even SAP HANA, SAS is addressing challenges in big data integration that we are researching in more depth for 2013. But SAS’ overall approach to data management aligns well to our information management research. I was impressed with SAS’ support for process and data orchestration and the overall ease of use of the product; it can be easily used by analysts and IT, with some great job monitoring capabilities.
For the chief marketing officer (CMO), SAS has expanded its Customer Intelligence Suite since my colleague Richard Snow assessed it last year. Expanded capabilities address a broad set of management and operational needs for marketing. SAS provides not just the analytics but campaign management, real-time decision management and personalization that helps ensure the best possible interaction and experience. Though it is not always seen as a key provider of applications for marketing, SAS has been steadily expanding its offerings organically and through acquisitions, and now, with a unified approach and user experience, is ready to strut its depth and sophistication, especially for B2C organizations.
SAS demonstrated a portfolio that engages everyone from the CMO to the analysts, managers and teams responsible for marketing activities that span from strategy and planning to interactions and ensuring great customer experience. An upcoming release expected in Q2 provides a new generation of user experience and integration that I have not seen in other offerings in the market. This sophisticated advancement in customer analytics aligns with my colleague Richard Snow’s view on the next generation of customer analytics that can leverage big data to meet forward-looking needs of organizations.
SAS sees the value in cloud computing, and now has its own global hosted technology infrastructure. It can help its customers set up a private cloud for its technology. SAS has had rapid global expansion to support
the cloud since our last assessment. I especially like its management of users, applications and technology and the ease of working across deployments and upgrades. SAS will soon also provide a platform for assembling applications for a range of needs for business. This new step forward, expected later in the year, is significant, as SAS is not known for its ability to foster the development of applications, but it has had this capability in its portfolio, and now is making it simpler and accessible in the cloud. Our research finds that the on-demand model and even software hosted by the supplier plays a growing role not just for analytics but for a range of big data and mobile technology needs in over a third of organizations. For SAS, this capability goes well beyond just providing analytics in the cloud, and places it in the market of companies such as Salesforce, which provides Force.com as its cloud-based application development environment but also provides information and analytics applications. SAS continues to expand its OnDemand offerings that provide easier access to many of the sophisticated solutions in its portfolio.
SAS is also applying analytics to decision-making through a series of advancements with its Decision Management technology. As many organizations realize, the value of analytics is in using them to enable action to be taken. This is no easy task, as most analytics and their presentation are not designed for assessing, taking and monitoring actions. SAS has developed a suite of capabilities and tools to help in the preparation of data, modeling, optimization, workflow and rules, monitoring and reporting, along with supporting case management. After a close look at the product I found it to be well-designed with an easy-to-use interface, especially the decision flow builder, which can be used by business analysts to design processes and analytics. I especially like the SAS Scenario Manager, which allows for side-by-side examination of decisions to determine how to optimize activities. SAS’ full suite of integrated decision management capabilities is expected to be available in the second quarter of this year, and SAS has an aggressive roadmap for continuous improvement. Only IBM in this market has a comparable area of focus and integrated approach with a portfolio of tools for decision management across any industry. SAS is making a smart step forward and will need to elevate the visibility of this offering in its portfolio to ensure it gets the proper level of consideration.
SAS also provides software for risk management, GRC and fraud technology to handle the most sophisticated challenges facing organizations and lower risk in organizations. Our research into GRC finds that 79 percent of organizations are looking to identify and manage risks faster, and more than half (59%) need to improve their control environment. I will let my colleague do further analysis of SAS portfolio in this area in the future.
SAS continues to build out its partner ecosystem. It has made strides to expand into other companies’ technology ecosystems, including Teradata and EMC, and works with system integrators such as Accenture, Capgemini and Deloitte. SAS had a great customer panel at the analyst event, and while I’m under NDA and cannot tell you the customer names, they represented some of the largest brands in the world, and they operate and use SAS to meet a variety of analytics and real-time operation needs.
The company has been steadily advancing, as we found in our Value Index for Business Intelligence last year. However, as SAS is adopted by more analysts, it will face the same issues I cited for business intelligence, which has not adapted well to business needs.
SAS has great potential with its approach to do more than just analyze the past but also predict and optimize future business activities using applications and tools that utilize its analytics backbone. SAS believes that its ability to handle proactive and forward-looking analysis on the largest of big data distinguishes it from other software providers along with using in-memory technology and makes it easy to try its software. SAS’ ability to use mathematics and embed predictive analytics into its offerings makes it a unique application provider. I could not cover all the key advancements in its portfolio but anyone that spends a little time examining their portfolio will realize there is a lot more to SAS than most realize. It’s broadening and deepening of its portfolio puts it on the short list of companies to consider for bringing more sophistication and science to business analytics.
Regards,
Mark Smith
CEO & Chief Research Officer
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