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William McKnight

Hello and welcome to my blog!

I will periodically be sharing my thoughts and observations on information management here in the blog. I am passionate about the effective creation, management and distribution of information for the benefit of company goals, and I'm thrilled to be a part of my clients' growth plans and connect what the industry provides to those goals. I have played many roles, but the perspective I come from is benefit to the end client. I hope the entries can be of some modest benefit to that goal. Please share your thoughts and input to the topics.

About the author >

William is the president of McKnight Consulting Group, a firm focused on delivering business value and solving business challenges utilizing proven, streamlined approaches in data warehousing, master data management and business intelligence, all with a focus on data quality and scalable architectures. William functions as strategist, information architect and program manager for complex, high-volume, full life-cycle implementations worldwide. William is a Southwest Entrepreneur of the Year finalist, a frequent best-practices judge, has authored hundreds of articles and white papers, and given hundreds of international keynotes and public seminars. His team's implementations from both IT and consultant positions have won Best Practices awards. He is a former IT Vice President of a Fortune company, a former software engineer, and holds an MBA. William is author of the book 90 Days to Success in Consulting. Contact William at wmcknight@mcknightcg.com.

Editor's Note: More articles and resources are available in William's BeyeNETWORK Expert Channel. Be sure to visit today!

As a couple of comments have indicated (link1, link2), the data mining capabilities of SQL Server 2005 are much improved. SQL Server 2000 had decision tree and clustering algorithms.

SQL Server 2005 adds these 5:
Time Series
Sequence Clustering
Naive Bayes
Association Rules
Neural Nets

Through the efforts of Microsoft in SQL Server 2005 as well as others before them like Polyvista, data mining is well on the way to being out of the back room with the scientists and into the hands of the analyst end-user.

Data mining is often the true analytical end result desired, yet many fear the complexities involved and do patchwork mining step-by-step, often bailing out before achieving the desired result or accepting a result with only the limited data that was able to be included without using true data mining.

Both data mining and desktop OLAP should be presented as first alternatives for end users, depending on the requirements of course. Education of end users will be key to acceptance,

Posted October 24, 2005 1:32 PM
Permalink | 2 Comments |


The white paper by PolyVista: Beyond Knowledge Discovery is an interesting one.

Thank you so much for pointing us to that site.

If you could have some comments on MS Excel 12 or Office 12, that would be great.

Does anybody have train and test data used in SQL Server 2005 Data Mining demo by Raman Lyer?

If yes, please e-mail to dispatch@reduct.com - can be flat file.

Thanks, Adam

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