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Wayne Eckerson

Welcome to Wayne's World, my blog that illuminates the latest thinking about how to deliver insights from business data and celebrates out-of-the-box thinkers and doers in the business intelligence (BI), performance management and data warehousing (DW) fields. Tune in here if you want to keep abreast of the latest trends, techniques, and technologies in this dynamic industry.

About the author >

Wayne has been a thought leader in the business intelligence field since the early 1990s. He has conducted numerous research studies and is a noted speaker, blogger, and consultant. He is the author of two widely read books: Performance Dashboards: Measuring, Monitoring, and Managing Your Business (2005, 2010) and The Secrets of Analytical Leaders: Insights from Information Insiders (2012).

Wayne is founder and principal consultant at Eckerson Group,a research and consulting company focused on business intelligence, analytics and big data.

Recently in Analytics Category


I don't think I've ever seen a market consolidate as fast the analytic platform market.

By definition, an analytic platform is an integrated hardware and software data management system geared to query processing and analytics that offers dramatically higher price-performance than general purpose systems. After talking with numerous customers of these systems, I am convinced they represent game-changing technology. As such, major database vendors have been tripping over themselves to gain the upper hand in this multi-billion dollar market.

Rapid Fire Acquisitions. Microsoft made the first move when it purchased Datallegro in July, 2008. But it's taken two years for Microsoft to port the technology to Windows and SQL Server so, ironically, it finds itself trailing the leaders. Last May, SAP acquired Sybase, largely for its mobile technology, but also for its Sybase IQ analytic platform, which has long been been the leading column-store database on the market and has done especially well in financial services. And SAP is sparking tremendous interest within its installed base for HANA, an in-memory appliance designed to accelerate query performance of SAP BW and other analytic applications.

Two months after SAP acquired Sybase, EMC snapped up massively parallel processing (MPP) database, Greenplum, and reportedly has done an excellent job executing new deals. Two months later, in September, 2010, IBM purchased the leading pureplay, Netezza, in an all cash deal worth $1.8 billion that could be a boon to Netezza if IBM can clearly differentiate between its multiple data warehousing offerings and execute well in the field.

And last month, Hewlett Packard, whose NeoView analytic platform died ingloriously last fall, scooped up Vertica, a market leading columnar database with many interesting scalability and availability features. And finally, Teradata this week announced it was purchasing AsterData, a MPP shared nothing database with rich SQL MapReduce functions that can perform deep analytics on both structured and unstructured data.

So, in the past nine months, the world's biggest high tech companies purchased five of the leading, pureplay analytic platforms. This rapid pace of consolidation is dizzying!

Consolidation Drivers

Fear and Loathing. Part of this consolidation frenzy is driven by fear. Namely, fear of being left out of the market. And perhaps fear of Oracle, whose own analytic platform, Exadata, has gathered significant market momentum, knocking unsuspecting rivals on their heels. Although pricey, Exadata not only fuels game-changing analytic performance, it now also supports transaction applications--a one-stop database engine that competitors may have difficulty derailing (unless Oracle shoots itself in the foot with uncompromising terms for licensing, maintenance, and proofs of concept.)

Core Competencies. These analytic platform vendors are now carving out market niches where they can outshine the rest. For Oracle, it's a high-performance, hybrid analytic/transaction system; SAP touts its in-memory acceleration (HANA) and a mature columnar database that supports real-time analytics and complex event processing; EMC Greenplum targets complex analytics against petabytes of data; Aster Data focuses on analytic applications in which SQL MapReduce is an advantage; Teradata touts its mixed workload management capabilities and workload-specific analytic appliances; IBM Netezza focuses on simplicity, fast deployments, and quick ROI; Vertica trumpets its scalability, reliability, and availability now that other vendors have added columnar storage and processing capabilities; Microsoft is pitching is PDW along with a series of data mart appliances and a BI appliance.

Pureplays Looking for Cover. The rush of acquisitions leaves a number of viable pureplays out in the cold. Without a big partner, these vendors will need to clearly articulate their positioning and work hard to gain beachheads within customer accounts. ParAccel, for example, is eyeing Fortune 100 companies with complex analytic requirements, targeting financial services where it says Sybase IQ is easy pickings. Dataupia is seeking cover in companies that have tens to hundreds of petabytes to query and store. Kognitio likes its chances with flexible cloud-based offerings that customers can bring inhouse if desired. InfoBright is targeting the open source MySQL market, while Sand Technology touts its columnar compression, data mart synchronization, and text parsing capabilities. Ingres is pursuing the open source data warehousing market, and its new Vectorwise technology makes it a formidable in-memory analytics processing platform.

Despite the rapid consolidation of the analytic platforms market, there is still obviously lots of choice left for customers eager to cash in on the benefits of purpose-built analytical machines that deliver dramatically higher price-performance than database management systems of the past. Although the action was fast and furious in 2010, the race has only just begun. So, fasten your seat belts as players jockey for position in the sprint to the finish.

Posted March 8, 2011 8:20 AM
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The purpose of business intelligence (BI) is to help organizations use information to make smart decisions. At a strategic level, BI is about making a business more intelligent. At a tactical level, it's about reporting and analysis.

BI professionals know better than anyone else that semantics are fickle. What's a customer? What's a sale? What's a product? Executives can wrangle for months before they agree on an exact definition of these household terms. And the same holds true for semantics within BI.

There has been a long succession of terms used to describe the reporting/analysis domain. (See figure 1.) Every decade, vendors with new technologies and experts with new theories conspire to create a new term to reinvigorate their products, ideas, and the field in general. Each new term creates a wave of hype and expectation, followed by some disenchantment as the organizations confront the harsh realities of implementing the BI flavor-of-the-day.

Figure 1. Evolution of BI Semantics
View image
Next week, I'll fill in the bottom half of this diagram and discuss trends in the BI vendor community.

1980s: Decision Support. Back in the 1980s, the industry's favored term was "decision support." But most "decision support" applications were custom built with hand code and cost a small fortune. This approach clearly didn't scale and couldn't support the aspirations of an emerging industry, and so the term eventually faded away.

1990s: Data Warehousing. In the early 1990s, Barry Devlin, Bill Inmon, and Ralph Kimball began writing about a new approach to reporting and analysis called "data warehousing" and the theory and term caught on. For the rest of the decade, IT professionals focused on getting data out of operational systems and into repositories optimized for query processing. But after the heavy lifting was done, IT professionals realized that simply building a data warehouse didn't guarantee that business people would use it.

2000s: Business Intelligence. So, in the early 2000s, IT professionals began focusing on making it easier for business users to access the data warehouse. They purchased desktop- and Web-based reporting and analysis tools and started talking about tools to make the business more intelligent. Soon, the term "business intelligence" became the industry watchword. (Note: I still use "business intelligence" to describe the entirety of the reporting/analysis domain because I believe it does the best job of describing the business purpose and value it has to offer.)

However, people quickly recognized that simply giving tools to business users doesn't guarantee that they'll use them or, if they do, find anything useful or act on what they've discovered. Soon, BI became shorthand for unwieldy reporting and analysis tools that often became expensive shelfware.

2005-2010: Performance Management. By the mid 2000s, the term business intelligence gave way to a new semantic upstart that focused on business outcomes. "Performance management" uses dashboards, scorecards, and planning tools align strategy with action and optimize performance at all levels of the organization. But executives soon recognized that defining metrics and targets that embody key objectives and goals is a top-down, slow-moving endeavor that is often subject to the vicissitudes of politics and bureaucracy.

2010s+: Analytics. Today, at the beginning of a new decade, a new term has emerged that emphasizes speed and agility and calls on organizations to move beyond monitoring performance to driving it. That term is "analytics."

Analytics initially referred to advanced statistical modeling using tools like SAS and SPSS. It gained preeminence thanks to an influential book written by Tom Davenport and Jeanne Harris titled "Competing on Analytics." Then, IBM began touting the power of analytics in television and magazine ads about the "Smarter Planet." Now, analytics refers to the entire domain of leveraging information to make smarter decisions. In other words, reporting and analysis.

2015+? In the future, perhaps we'll complete the circle and call our domain "decision support" once again. But whatever the term, the value is undeniable and enduring: using information to make better decisions is perhaps the last great frontier of sustainable competitive advantage.

Posted February 22, 2011 7:07 AM
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