The document is a presentation on data mining using Excel 2010 and PowerPivot, covering definitions, tasks, and capabilities of data mining algorithms. It highlights various data mining techniques such as supervised and unsupervised learning, forecasting, and the use of PowerPivot for processing large datasets. Additionally, it provides resources and contact information for further exploration and learning.

1. Data Mining
with Excel 2010
and PowerPivot
Mark Tabladillo Ph.D.
http://marktab.net
September 18, 2010

2. SQL Saturday 46 -- Raleigh NC
#sqlsat46
© 2010 Mark Tabladillo Ph.D.
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3. MarkTab & Data Mining
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4. © 2010 Mark Tabladillo Ph.D.
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5. © 2010 Mark Tabladillo Ph.D.
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6. Outline
© 2010 Mark Tabladillo Ph.D.
What is What is
Demos
Data Mining PowerPivot
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7. Data Mining as a Service
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8. Outline
© 2010 Mark Tabladillo Ph.D.
What is What is
Demos
Data Mining PowerPivot
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9. Data Mining Definitions
• Data mining
• Machine Learning
• Data mining algorithms -- typically use estimation or
optimization to achieve results (as opposed to only
calculations).
© 2010 Mark Tabladillo Ph.D.
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10. Data Mining Tasks
• Supervised
• Answer known, what is correlated?
• Unsupervised
• Answer unknown (unspecified), what are the groups?
• Forecasting
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• Given a trend, what is next?
Value
Slide
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11. Data Mining Add-In for Excel
• Requires Analysis Services instance
• Version 10.00.2531.00 (April 2009)
• 32-Bit Add-In
• Microsoft .NET Framework 2.0 (32-bit)
• Office 2007 (Professional, Professional Plus, Ultimate,
© 2010 Mark Tabladillo Ph.D.
Enterprise)
• SQL Server Enterprise or Standard (or Developer) 2008 or
higher
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12. The Analyze Tab
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13. The Analyze Tab
Menu Option Data Mining Algorithm
Analyze Key Influencers Naïve Bayes
© 2010 Mark Tabladillo Ph.D.
Detect Categories Clustering
Fill from Example Logistic Regression
Forecast Time Series
Highlight Exceptions Clustering
Scenario Analysis (Goal Seek) Logistic Regression
Scenario Analysis (What If) Logistic Regression
Prediction Calculator Logistic Regression
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Shopping Basket Analysis Association Rules

14. Data Mining Tab
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15. Data Mining Tab
Many
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16. Data Mining Capacities
SQL Server 2008 R2 Analysis Services
Maximum sizes/numbers
Object
Maximum data mining models per
2^31-1 = 2,147,483,647
structure
Maximum data mining structures per
© 2010 Mark Tabladillo Ph.D.
2^31-1 = 2,147,483,647
solution
Maximum data mining structures per
2^31-1 = 2,147,483,647
Analysis Services database
Maximum data mining attributes
2^31-1 = 2,147,483,647
(variables) per structure
Reference:
http://www.marktab.net/datamining/index.php/2010/08/01/sql-server-
data-mining-capacities-2008-r2/ 16

17. Data Mining Tab
© 2010 Mark Tabladillo Ph.D.
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18. Outline
© 2010 Mark Tabladillo Ph.D.
What is What is
Demos
Data Mining PowerPivot
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19. PowerPivot for Excel
• Take advantage of familiar Excel tools and
features
• Process massive amounts of data in seconds
• Load even the largest data sets from virtually any
© 2010 Mark Tabladillo Ph.D.
source
• Use powerful new analytical capabilities, such as
Data Analysis Expressions (DAX)
• Make the most of multi-core processors and
gigabytes of memory
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20. PowerPivot for Excel Sources
• SQL Server
• SQL Azure
• Oracle, Teradata, Sybase, Informix, IBM DB2
• OLEDB/ODBC
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• Analysis Services (SSAS)
• Reporting Services (SSRS)
• Excel, Text File
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21. PowerPivot Reference
• http://www.powerpivot.com (Product Site)
• http://www.powerpivotpro.com (Blog Site)
© 2010 Mark Tabladillo Ph.D.
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22. Outline
© 2010 Mark Tabladillo Ph.D.
What is What is
Demos
Data Mining PowerPivot
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23. Resources
• MarkTab.NET
Blog, links, video resources and information for
data mining
• Blog: http://marktab.net/datamining
© 2010 Mark Tabladillo Ph.D.
• Twitter: @MarkTabNet
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24. © 2010 Mark Tabladillo Ph.D.
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25. Regroup and Conclusion
• Main Points from this Presentation
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26. Contact Information
• Mark Tabladillo
http://marktab.net
• Also on:
Twitter @marktabnet
© 2010 Mark Tabladillo Ph.D.
Linked In
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