Microsoft Puts Data Mining Front and Center

Company allies with partners to define XML for Analysis specification

Microsoft has garnered some heavy-hitting support for its efforts to incorporate data-mining technology into its XML for Analysis specification. The company recently announced that the SAS Institute has joined the XML for Analysis (XML/A) Council as a co-chair. (You can read more about the XML/A Council at the URL listed in the Resources section at the end of this article.)

The fact that SAS has joined the XML/A Council is noteworthy for two reasons. First, SAS has a major market-share position in the OLAP and data-mining industry. Interoperability technologies are meaningless if they don't allow cross-platform interoperability, so SAS's strong support for the specification makes XML for Analysis more viable as a cross-platform interoperability tool. Second, and perhaps more important, SAS brings a wealth of practical data-mining experience to the table. Microsoft can leverage this experience as the company adds rich data-mining support to the XML for Analysis specification.

XML for Analysis is a set of XML Message Interfaces that uses the industry standard Simple Object Access Protocol (SOAP) to define the data-access interaction between a client application and an analytical data provider. In other words, XML for Analysis lets clients and servers from different vendors communicate with one another while processing OLAP and data-mining data.

When I spoke about the SAS announcement with Sheryl Tullis, a SQL Server program manager, she emphasized that Microsoft views the data-mining market as incredibly strategic for the company and its customers. I couldn't agree more: Data-mining capability allows more sophisticated analysis than OLAP does.

Most IT shops can use OLAP in multiple ways to help their organizations make better decisions. But I think that OLAP approaches to data exploration are most effective when you know what questions are important to ask. Unfortunately, data analysts don't always know which question will point to the needle in the haystack that they're looking for. I look at data mining as a set of technologies that can help show me the answer when I don't even know what the question is.

SQL Server 2000's support of data mining made the technology available to mass-market users for the first time, but data mining is still an underused technology. Microsoft's addition of data-mining support in the XML for Analysis specification won't immediately affect the deployment of data-mining technology in mainstream IT departments. However, the specification's new cross-platform data-mining support will let tool vendors more easily create innovative solutions that leverage data-mining server technology from all of the major players. Over time, this innovation will create a rich tool market for customers, which is a necessary milestone before data mining becomes a common, day-to-day approach for understanding our data.

XML for Analysis Council

"Microsoft, Hyperion Welcome SAS as Co-Chair on XML for Analysis Council"

"XML for Analysis Specification"

Support Webcast: Introduction to XML for Analysis Services
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