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Building Data Mining Solutions With OLE DB for DM and XML for Analysis

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Data Mining and Knowledge Discovery Handbook

Abstract

Data Mining component is included Microsoft SQL Server 2000, on of the most popular DBMS. This gives a push for Data Minwg technologies moving from niche towards mainstream. Apart from a few algorithms, the main contribution of SQL Server Data Mining is the implementation of OLE DB for Data Mining. OLE DB for Data mining is an industrial standard lead by Microsoft and supported by a number of ISVs. It leverages from two existing relational technology: SQL and OLE DB. It defines a SQL language for data mining query based on relational concept. More recently, Microsoft, Hyperion, SAS and a few other BI vendors formed the XML for Analysis Council. The XML for Analysis covers both OLAP and Data Mining. The goal is to allow consumer applications to query various BI packages from different platform. This chapter gives an overview of OLE DB for Data Mining and XML for Analysis. It also shows how to build Data Mining application using these APIs.

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References

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© 2005 Springer Science+Business Media, Inc.

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Tang, Z., Maclennan, J., Kim, P.(. (2005). Building Data Mining Solutions With OLE DB for DM and XML for Analysis. In: Maimon, O., Rokach, L. (eds) Data Mining and Knowledge Discovery Handbook. Springer, Boston, MA. https://doi.org/10.1007/0-387-25465-X_64

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  • DOI: https://doi.org/10.1007/0-387-25465-X_64

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-24435-8

  • Online ISBN: 978-0-387-25465-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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