DALLAS, May 24, 1999 — Microsoft Corp. today announced a new initiative to extend OLE DB data access interfaces, providing software vendors and application developers with an open interface to more efficiently integrate data mining tools and applications. A joint effort between the Microsoft® SQL Server TM development group and Microsoft Research, OLE DB for data mining exemplifies Microsoft’s commitment to delivering leading-edge technology to the developer community.
Data mining technology provides sophisticated analysis and knowledge-discovery capabilities for applications such as data warehouses and customer relationship management (CRM) systems. A shared data access interface will enable many diverse data mining products to more easily exchange data and results, and will enable ISVs to more easily integrate data mining technology into line-of-business solutions. This advance will enable customers to transparently access sophisticated solutions like fraud detection, credit-risk analysis, marketing campaign management, one-to-one marketing and adaptive Web content from existing line-of-business applications.
“The data mining industry today is highly fragmented, making it difficult for application software vendors and corporate developers to integrate different knowledge-discovery tools,”
said Tod Nielsen, vice president of marketing for the Developer Division at Microsoft.
“A common interface for data mining will enable developers to easily embed highly scalable data mining capabilities into their existing applications, giving a much larger audience of users access to these sophisticated capabilities.”
OLE DB for data mining will build upon Microsoft’s Universal Data Access strategy, which includes the industry standard OLE DB for OLAP interface for multidimensional database access. Typically, data mining tools require different data formats from those available in relational or multidimensional (OLAP) database systems. The data mining extensions to OLE DB will provide a format common to existing tools and applications such as statistical analysis, pattern recognition, data prediction and segmentation methods, and visualization products.
“Microsoft’s OLE DB extensions for data mining will address the complexity, cost and lack of standardization that have been barriers to broader market acceptance of data mining in the past,”
said Eric Apps, president of Toronto-based data mining vendor ANGOSS Software Corp.
“These extensions will enable more affordable and powerful solutions, which will accelerate the integration of data mining technology with other enterprise applications. ANGOSS fully supports and will continue to build on Microsoft’s important initiatives in this area.”
The data mining extensions to OLE DB are being examined by a group of data mining software vendors as part of Microsoft’s open review process. In June, Microsoft will hold a design review to solicit additional comments from the industry before publishing a draft specification for public review. Final publication of the specification is expected in the second half of 1999. Microsoft also announced today that version 2.0 of the OLE DB for OLAP specification was under review after incorporating feedback from the more than 40 software vendors supporting the interface.
About Microsoft SQL Server
Created by a world-class development team, Microsoft SQL Server 7.0 is a leading Windows NT® Server operating system-based database, bringing business advantage and improved decision-making to all levels of the organization through the power of data warehousing, industry solutions and interoperability with Microsoft Office. Microsoft SQL Server is a member of the Microsoft BackOffice® family, a set of servers that make it easy to build, manage and deploy powerful business solutions.
About Microsoft Research
Microsoft Research has been active in the data mining field since 1996. Led by industry-renowned researcher Usama Fayyad, the data mining team has already delivered data mining functionality as a component of Microsoft Site Server 3.0 Commerce Edition. One such feature, Intelligent CrossSell, uses previous shopper trends to automatically make recommendations for dynamic merchandising supporting easy, real-time administration of product and price promotions from any remote Web browser.
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