Visual Numerics integration into SQL Server Data Mining


Our friends at Visual Numerics, Inc have created an excellent white paper covering the creation of SQL Server Data Mining plug-in algorithms in C#.  In addition to documenting all of the architecture and concepts required, they have created a step-by-step tutorial demonstrating how to integrate their own K-Means clustering algorithm into SQL Server Data Mining using the C# interfaces.  The entire data mining team here in SQL Server reviewed the paper – we couldn’t have done a better job ourselves!  Kudos to VNI for such an accomplishment!

The paper includes FULL SOURCE CODE for their plug-in algorithm and is available at http://www.vni.com/company/whitepapers/MicrosoftBIwithNumericalLibraries.pdf.  Of course you will need to get a copy of their IMSL C# Numerical Library, for which an eval copy is available upon request to VNI.

As a teaser, here is the TOC for their paper:

Audience ……………………………………………………………………………………….. 4
Rationale ……………………………………………………………………………………….. 4
Background ……………………………………………………………………………………. 5
Plug‐in Architecture ………………………………………………………………………… 8
Managed Plug‐in Development ………………………………………………………… 9
IMSL C# Library: ClusterKMeans Integration……………………………………. 9
Starting up…………………………………………………………………………………. 10
Metadata Changes (Metadata.cs) ………………………………………………… 10
Algorithm Changes (Algorithm.cs) ………………………………………………… 11
Training and Persistence of patterns…………………………………………….. 11
Persistence of Patterns ……………………………………………………………….. 13
Prediction………………………………………………………………………………….. 13
Algorithm Navigator Changes (AlgorithmNavigator.cs) …………………… 13
Registering the Algorithm with Analysis Services……………………………. 14
Debugging …………………………………………………………………………………. 15
Other Default Features for Third‐Party Mining Algorithm Developers…. 16
The User Experience ……………………………………………………………………… 16
Excel 2007 …………………………………………………………………………………. 19
Conclusion……………………………………………………………………………………. 21
About the Author………………………………………………………………………….. 21
References …………………………………………………………………………………… 22
Appendix A: Code Files ………………………………………………………………….. 23