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Microsoft has been steadily pouring money into big data and business intelligence. The company of course owns the most widely used analytical tool in the world, Microsoft Excel, which our benchmark research into Spreadsheets in the Enterprise shows is not going away soon. User resistance (cited by 56% of participants) and lack of a business case (50%) are the most common reasons that spreadsheets are not being replaced in the enterprise. The challenge is ensuring the spreadsheets are not just personally used but connected and secured into the enterprise for a range of consistency and potential errors that all add up to more work and maintenance as my colleague has pointed out recently.
Along with Microsoft SQL and SharePoint, Excel is at the heart of the company’s BI strategy. In particular, PowerPivot, originally introduced as an add-on for Excel 2010 and built into Excel 2013, is a discovery tool that enables exploratory analytics and data mashups. PowerPivot uses an in-memory, column store approach similar to other tools in the market. Its ability to access multiple data sources including from third parties and government through Microsoft’s Azure Marketplace, enables a robust analytical experience.
Ultimately, information sources are more important than the tool sets used on them. With the Azure Marketplace and access to other new data sources such as Hadoop through partnership with Hortonworks as my colleague assessed, Microsoft is advancing in the big data space. Microsoft has partnered with Hortonworks to bring Hadoop data into the fold through HDInsights, which enable familiar Excel environments to access HDFS via HCatalog. This approach is similar to access methods utilized by other companies, including Teradata which I wrote about last week. Microsoft stresses the 100 percent open source nature of the Hortonworks approach as a standard alternative to the multiple, more proprietary Hadoop distributions occurring throughout the industry. An important benefit for enterprises with Microsoft deployments is that Microsoft Active Directory adds security to HDInsights.
As my colleague Mark Smith recently pointed out about data discovery methods, the analytic discovery category is broad and includes visualization approaches. On the visualization side, Microsoft markets PowerView, also part of Excel 2013, which provides visual analytics and navigation on top of the Microsoft’s BI semantic model. Users also can annotate and highlight content and then embed it directly into PowerPoint presentations. This direct export feature is valuable because PowerPoint is still a critical communication vehicle in many organizations. Another visual tool, currently in preview, is the Excel add-in GeoFlow, which uses Bing Maps to render visually impressive temporal and geographic data in three dimensions. Such a 3-D visualization technique could be useful in many industries. Our research into next generation business intelligence found that deploying geographic maps (47%) and visualizing metrics on them (41%) are becoming increasing important but Microsoft will need to further exploit location-based analytics and the need for interactivity.
Microsoft has a core advantage in being able to link its front-office tools such as Excel with its back-end systems such as SQL Server 2012 and SharePoint. In particular, having the ability to leverage a common semantic model through Microsoft Analytical Services, in what Microsoft calls its Business Intelligence Semantic Model, users can set up a dynamic exploratory environment through Excel. Once users or analysts have developed a BI work product, they can publish the work product such as a report directly or through SharePoint. This integration enables business users to share data models and solutions and manage them in common, which applies to security controls as well as giving visibility into usage statistics to see when particular applications are gaining traction with organizational users.
Usability, which our benchmark research into next-generation business intelligence identifies as the number-one evaluation criterion in nearly two-thirds (64%) of organizations, is still a challenge for Microsoft. Excel power users will appreciate the solid capabilities of PowerPivot, but more casual users of Excel – the majority of business people – do not understand how to build pivot tables or formulas. Our research shows that only 11 percent of Excel users are power users and most skill levels are simply adequate (49%) compared to above average or excellent. While PowerView does give some added capability, a number of other vendors of visual discovery products like Tableau have focused on user experience from the ground up, so it is clear that Microsoft needs to address this shortcoming in its design environment.
When we consider more advanced analytic strategies and inclusion of advanced algorithms, Microsoft’s direction is not clear. Its Data Analysis eXpressions (DAX) can help create custom measures and calculated fields, but it is a scripting language akin to MDX. This is useful for IT professionals who are familiar with such tools, but here also business-oriented users will be challenged in using it effectively.
A wild card in Microsoft’s BI and analytics strategy is with mobile technology. Currently, Microsoft is pursuing a build-once, deploy-anywhere model based on HTML5, and is a key member of the Worldwide Web Consortium (W3C) that is defining the standard. The HTML5 standard, which has just passed a big hurdle in terms of candidate recommendation is beginning to show value in the design of new applications that can be access through web-browsers on smartphones and tablets. However, the success or failure of its Windows 8-based Surface tablet will be the real barometer since its integration with the Office franchise is a key differentiator. This approach of HTML5 could be challenging as our technology innovation research into mobile technology finds more organizations (39%) prefer native mobile applications from the vendors specific application stores compared to 33 percent through web-browser based method and a fifth with no preference. Early adoption of the tablet has not been strong, but Microsoft is said to be doubling down with a new version to be announced shortly. Success would put Office into the hands of the mobile workforce on a widespread basis via Microsoft devices, which could have far-reaching impacts for the mobile BI market.
As it stands now, however, Microsoft faces an uphill battle in establishing its mobile platform in a market dominated by Android and Apple iOS devices like the iPhone and iPad. If the Surface ultimately fails, Microsoft will likely have to open up Office to run on Android and iOS or risk losing its dominant position. My colleague is quite pessimistic about Microsoft overall mobile technology efforts and its ability to overcome the reality of the existing market. Our technology innovation research into mobile technology finds that over half of organizations have a preference for their smartphone and tablet technology platform, and the first ranked smartphone priorities has Apple (50%), Android (27%) and RIM (17%) as top smartphone platforms with Microsoft a distant fourth (5%); for tablets is Apple (66%), Android (19%) and then Microsoft (8%). Based on these finding, Microsoft faces challenges on both the platform front and if they adapt their technology to support others that are more preferred and used in business today.
Ultimately, Microsoft is trying to pull together different initiatives across multiple internal business units that are known for being very siloed and not organized well for customers. Ultimately, Microsoft has relied on its channel partners and customers to figure out how to not just make them work together but also think about what is possible since they are not always given clear guidance from Redmond. Recent efforts find that Microsoft is trying to come together to address the big data and business analytics challenge and the massive opportunity it represents. One area in which this is coming together is Microsoft’s cloud initiatives. Last year’s announcements of Azure virtual machines enables an infrastructure-as-a-service (IaaS) play for Microsoft and positions Windows Azure SQL Database as a service. This could make the back end systems I’ve discussed available through a cloud-based. Ironically, the cloud-based Office365 suite does not include core productivity applications such as Excel and PowerPoint, so front-end access will still come through the client version of the software.
For organizations that already have installed Microsoft as their primary BI platform and are looking for tight integration with an Excel-based discovery environment, the decision to move forward is relatively simple. The trade-off is that this package is still a bit IT-centric and may not attract as many in the larger body of business users as a more user-friendly discovery product might do and address the failings of business intelligence. Furthermore, since Microsoft is not as engaged in direct support and service as other players in this market, it will need to move the traditionally technology focused channel to help their customers become more business savvy. For marketing and other business departments, especially in high-velocity industries where usability and time-to-value is at a premium and back-end integration is secondary, other tools will be worth a look. Microsoft has great potential and with analytics being the top ranked technology innovation priority among its customers I hope that the many divisions inside the global software giant can finally come together to deliver a comprehensive approach.
VP and Research Director
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.
CEO & Chief Research Officer