sql saturday 119 chicago -- enterprise data mining with sql server

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This presentation covers SQL Server 2012 data mining -- mostly demo (therefore not in slides) -- an earlier version is on video at http://channel9.msdn.com/Events/TechEd/NorthAmerica/2011/DBI326

TRANSCRIPT

Enterprise Data Mining with SQL Server

Mark Tabladillo Ph.D.Microsoft MVPMarkTab Consulting

SQL Saturday 119 Chicago, ILMay 19, 2012

About Mark Tabladillo

20 Years in Atlanta, Georgia Consulting since 1998; Incorporated 2003 Part-Time Faculty at University of Phoenix

SAS and Microsoft Expert Presenter Microsoft TechEd; SAS Global Forum; Predictive

Analytics World Taught statistics at undergraduate and graduate level Blog: http://marktab.net @MarkTabNet

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Enterprise:Leaders of Leaders of

Leaders

Enterprise Challenge

Enterprise Challenge

Enterprise Challenge

Enterprise Challenge

“Data Mining”

Definitions

Phrase Goal

“Data Mining” Inform actionable decisions

“Machine Learning”

Determine best performingalgorithm

SQL Server 2012

Physical and Logical

OLAP EnginePhysical Architecture

http://msdn.microsoft.com/en-us/library/ms174776.aspx

Analysis Services Logical Architecture http://msdn.microsoft.com/en-us/library/ms174587.aspx

Outline

Contoso Retail and Fundamentals Enterprise-Level Data Mining Demo for

SQL Server What is my next step?

What is Contoso Retail?

Demonstration dataset for SQL Server Database Engine and Analysis Services

http://www.microsoft.com/downloads/en/details.aspx?displaylang=en&FamilyID=868662dc-187a-4a85-b611-b7df7dc909fc

What are the fundamentals?

Reading

Writing

Arithmetic

‘Readin’

‘Ritin’

‘Rithmetic

What Enterprise Tools support Data Mining?

SQL Server Management Studio (SSMS) SQL Server Data Tools (SSDT)

Business Intelligence Development Studio (BIDS) SQL Server Integration Services (SSIS)

PowerShell version 2

What Enterprise Tools support Data Mining?

Data Mining

SSMS SSIS PowerShell

Variable 0 1 2 3 4 5 6 7

DiscretizedDiscretizedContinuousDiscrete

Variable 0 1 2 3 4 5 6 7

DiscretizedDiscretizedContinuousDiscrete

Variable 0 1 2 3 4 5 6 7

DiscretizedDiscretizedContinuousDiscrete

Variable 0 1 2 3 4 5 6 7

DiscretizedDiscretizedContinuousDiscrete

Variable 0 1 2 3 4 5 6 7

DiscretizedDiscretizedContinuousDiscrete

Documentation for SQL Server 2012

Data Mining Structures http://msdn.microsoft.com/en-

us/library/cc645741.aspx http://msdn.microsoft.com/en-

us/library/ms174757.aspx Data Mining Models http://msdn.microsoft.com/en-

us/library/cc645779.aspx

Contoso Retail:Enterprise Data Mining

Demonstration

What is my next step?

SQL Server 2012 Enterprise (includes database engine, Analysis Services, SSMS and SSDT) http://www.microsoft.com/sqlserver/en/us/get-sql-

server/try-it.aspx Microsoft Office 2010 Professional http://office.microsoft.com/en-us/try

PowerShell 2.0 http://support.microsoft.com/kb/968929

Data Mining Portal and Blog http://www.marktab.net

Data mining leaders can tackle enterprise data mining challenges with SQL Server Management Studio SQL Server Data Tools PowerShell version 2

Become leaders of leaders of leaders

Conclusion

Where Can I Find More Information?

http://marktab.net Data Mining Resource http://marktab.net/datamining Data Mining

Blog http://sqlserverdatamining.com SQL Server

Data Mining http://technet.microsoft.com Microsoft’s

TechNet

Graphics

Ship graphics Copyright © 1995-2006 Nova Development and its licensors. All rights reserved. Used with permission.

Abstract

This presentation introduces SQL Server Data Mining (SSDM) for SQL Server Professionals based on the speaker's past presentation for Microsoft TechEd. Starting with SQL Server Management Studio (SSMS), the demo includes the interfaces important for professional development, including Business Intelligence Development Studio (BIDS), highlighting Integration Services, and PowerShell. The interactive demos are based on Microsoft's Contoso Retail sample data. Finally we will evaluate where Microsoft data mining can help you in a practical business environment, which may include Oracle and SAS.

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