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Secrets of Enterprise Data Mining
The document presents insights on enterprise data mining, particularly focusing on tools offered by Microsoft and their applications in various industries. It emphasizes the ability to scale data mining efforts from Excel add-ins to production environments using SQL Server 2012 tools. The document also highlights Microsoft's competitive stance in analytics and details on semantic search capabilities and resources available for data mining training and consulting.
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Secrets of Enterprise Data Mining
- 1. Secrets of Enterprise DataMining Mark Tabladillo, Ph.D. (MVP, MCAD .NET, MCITP, MCT) PASS SQL Saturday #177 Mountain View, CA February 23, 2013
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- 3. About MarkTab Training andConsulting with Ph.D. – Industrial Engineering, http://marktab.com Georgia Tech Data Mining Resources and Blog at Training and consulting http://marktab.net internationally across many industries – SAS and Microsoft Contributed to peer-reviewed research and legislation Mentoring doctoral dissertations at the accredited University of Phoenix Presenter
- 4. Interactive Name (up to)three things you want from enterprise data mining
- 5. Secret: Excel data mining Exceladd-in for SQL Server data mining
- 6. Secret: More thanjust SQL Server Microsoft continues to add machine learning technology
- 7. Microsoft Offers Bing Maps Xbox Kinect Hacker Magnet SQL Server 2012 Analysis Services (Multidimensional and Data Mining) Integration Services Semantic Search Hadoop Partnership Excel Projects from Microsoft Research
- 8. Definitions What is datamining?
- 9. Definition Data mining isthe automated or semi-automated process of discovering patterns in data Machine learning is the development and optimization of algorithms for automated or semi-automated pattern discovery
- 10. Purposes Phrase Goal “Data Mining” Inform actionable decisions “Machine Determine best performing Learning” algorithm
- 11. Secret: Give artistsart Data mining is part of a complete decision cycle
- 12. MarkTab Decision Cycle GO Synthesis Analysis (art) (science) Science needs science fiction -- MarkTab
- 13. MarkTab Decision Cycle GO Synthesis Analysis (art) (science)
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- 17. Secret: Microsoft isan analytics competitor Industry Comparisons 2012-2013
- 18. Gartner 2013 Magic Quadrant for Business Intelligence and Analytics Platforms Retrieved from http://www.gartner.com/technology/reprints.do?id=1-1DZLPEH&ct=130207&st=sb – February 5, 2013
- 19. Gartner 2013 Magic Quadrant for Data Warehouse Database Management Systems Retrieved from http://www.gartner.com/technology/reprints.do?id=1-1DU2VD4&ct=130131&st=sb – January 31, 2013
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- 21. SQL Server 2012 BusinessIntelligence and Business Analytics
- 22. New Platform options:managed services Platform Infrastructure Platform Software (Self Managed) (as a Service) (as a Service) (as a Service) Applications Applications Applications Applications Data Data Data Data Runtime Runtime Runtime Runtime Middleware Middleware Middleware Middleware Managed Services Database Database Database Database Managed Services O/S O/S O/S O/S Virtualization Virtualization Virtualization Virtualization Managed Services Servers Servers Servers Servers Storage Storage Storage Storage Networking Networking Networking Networking
- 23. SQL Release timelines 2008 SQL Server 2008 2012 SQL Server 2012 AlwaysOn Columnstore 1989 1993 2000 Sparse Columns FileTable SQL Server 1.0 SQL Server 4.21 1996 SQL Server 2000 Spatial Types Semantic Search (OS/2) (NT) SQL Server 6.5 Reporting Services FILESTREAM Power View 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 1991 1995 1998 2005 2010 SQL Server 1.1 SQL Server 6.0 SQL Server 7.0 SQL Server 2005 SQL Server 2008 R2 (OS/2) Dynamic Locking Unicode Support Data-tier Apps Auto-Tuning Native XML StreamInsight Full-text search SQLCLR PowerPivot Replication Service Broker Master Data Services Analysis Services Integration Services Aug 11 Aug 10 New Portal Experience SQL Azure SU4 RTW Feb 11 Sparse Columns Database Copy SQL Azure Reporting CTP2 SQL Azure Reporting CTP3 Web Admin Dec DataSync CTP2 Update 10 SQL Azure DataSync CTP3 Apr 10 Feb 10 SQL Azure SU2 RTW Jul 10 SQL Azure SU6 RTW DAC Import/Export Service SQL Azure RTW MARS DataSync CTP1 DataSync CTP2 Denali TSQL Apr 10 Jul 10 Oct 10 Jan 11 Apr 11 Jul 11 Oct 11 Feb 10 Jun 10 Nov 10 Apr 11 SQL Azure SU1 RTW SQL Azure SU3 RTW DataMarket RTW SQL Azure SU V.Next Alter Edition 50 GB Db SQL Azure Reporting CTP1 Multiple Servers Spatial Type Server Mgmt API HierarchyId Type JDBC DAC Upgrade
- 24. Secret: Many already haveMicrosoft analytics Business Intelligence and Business Analytics are included with most SQL Server licenses
- 25. Data platform: SQLServer 2012 Data Integration Database Services Analytical Services Reporting Services Services SQL Server* Integration Services* Reporting Services* Analysis Services* SQL Azure* SQL Azure Reporting* Master Data Services* Replication Data Mining Report Builder SQL Azure Data Sync* Data Quality Services* Full Text & Semantic StreamInsight* PowerPivot* Power View* Search* Project “Austin”* * New / improved in SQL Server 2012
- 26. SQL Server 2012Editions Retrieved from http://www.microsoft.com/en-us/sqlserver/editions.aspx -- February 2013
- 27. Secret: Microsoft offers threeenterprise tools All three tools support scaled solutions
- 28. What Enterprise Toolssupport Microsoft Data Mining? Data Mining SSMS SSIS PowerShell
- 29. Variable 0 1 2 3 4 5 6 7 Discretized Discretized Continuous Discrete
- 30. Variable 0 1 2 3 4 5 6 7 Discretized Discretized Continuous Discrete
- 31. Variable 0 1 2 3 4 5 6 7 Discretized Discretized Continuous Discrete
- 32. Variable 0 1 2 3 4 5 6 7 Discretized Discretized Continuous Discrete
- 33. Data Mining Capacities SQL Server 2008 R2 Analysis Services Object Maximum sizes/numbers Maximum data mining models per structure 2^31-1 = 2,147,483,647 Maximum data mining structures per solution 2^31-1 = 2,147,483,647 Maximum data mining structures per Analysis 2^31-1 = 2,147,483,647 Services database Maximum data mining attributes (variables) per 2^31-1 = 2,147,483,647 structure Reference: http://www.marktab.net/datamining/index.php/2010/08/01/sql-server-data-mining-capacities-2008-r2/
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- 35. Future: Most datais Text Two Research Types • Quantitative research = data mining • Qualitative research = text mining The future is combining both
- 36. Full-Text Search Enhancements Propertysearch: search on tagged properties (such as author or title) Customizable NEAR: find words or phrases close to one another New Word Breakers and Stemmers (for many languages)
- 37. (iFilter Required) iFilters Full-Text Documents Keyword Index “FTI” Semantic Key Phrase Semantic Index – Semantic Document Database Tag Index Similarity Index “DSI” “TI”
- 38. Languages Currently Supported TraditionalChinese Simplified Chinese German British English English Portuguese French Chinese (Hong Kong SAR, PRC) Italian Spanish Brazilian Chinese (Singapore) Russian Chinese (Macau SAR) Swedish
- 39. Phases of SemanticIndexing Full Text Keyword Index “FTI” Semantic Document Similarity Index “DSI” Semantic Key Phrase Index – Tag Index “TI” http://msdn.microsoft.com/en-us/library/gg492085.aspx#SemanticIndexing
- 40. Secret: Semantic Search scaleslinearly Performance
- 41. Integrated Full TextSearch (iFTS) Improved Performance and Scale: Scale-up to 350M documents for storage and search iFTS query performance 7-10 times faster than in SQL Server 2008 Worst-case iFTS query response times less than 3 sec for corpus Similar or better than main database search competitors (2012, Michael Rys, Microsoft)
- 42. Linear Scale ofFTI/TI/DSI First known linearly scaling end-to-end Search and Semantic product in the industry Time in Seconds vs. Number of Documents (2011 – K. Mukerjee, T. Porter, S. Gherman – Microsoft)
- 43. Text Mining References Video http://channel9.msdn.com/Shows/DataBound/DataBound-Episode-2-Semantic- Search http://www.microsoftpdc.com/2009/SVR32 Semantic Search (Books Online) – explains the demo http://msdn.microsoft.com/en-us/library/gg492075.aspx Paper http://users.cis.fiu.edu/~lzhen001/activities/KDD2011Program/docs/p213.pdf
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- 45. Software SQL Server 2012Enterprise (includes database engine, Analysis Services, SSMS and SSDT) http://www.microsoft.com/sqlserver/en/us/get-sql-server/try-it.aspx Microsoft Office 2012 Professional http://office.microsoft.com/en-us/try
- 46. Organizations Professional Associationfor SQL Server http://www.sqlpass.org Atlanta MDF http://www.atlantamdf.com/ Atlanta Microsoft BI Users Group http://www.meetup.com/Atlanta-Microsoft- Business-Intelligence-Users/ PASS Business Analytics Conference http://www.passbaconference.com Microsoft TechEd North America http://northamerica.msteched.com/
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- 48. Conclusion: Seven Secrets Exceldata mining More than just SQL Server Success involves everyone Microsoft is an analytics competitor Many already have Microsoft analytics Microsoft offers three enterprise tools Semantic search scales linearly
- 49. Connect Data Mining Resourcesand blog http://marktab.net Data Mining Training and Consulting (especially Microsoft and SAS) http://marktab.com
- 50. Abstract If you havea SQL Server license (Standard or higher) then you already have the ability to start data mining. In this new presentation, you will see how to scale up data mining from the free Excel 2013 add-in to production use. Aimed at beginning to intermediate data miners, this presentation will show how mining models move from development to production. We will use SQL Server 2012 tools including SSMS, SSIS, and SSDT.