BEGIN:VCALENDAR VERSION:2.0 PRODID:-//SQLBits/com CALSCALE:GREGORIAN METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VEVENT DTSTART:20130503T111000Z DTEND:20130503T121000Z LOCATION:SQLBits Conference - Suite 1 SUMMARY:Cleaning Up Dirty Data with SSIS DESCRIPTION:Dirty data is everywhere, and it's headed for a database near you.  Extraction, transformation, and loading (ETL) can be difficult, but often the most challenging component of that process is the validation and clean up of data. Information must be cleansed in such a way that it retains its original message and business value, while conforming to the expectations of the destination system(s). 


In this session, we'll discuss some design patterns for addressing different types of dirty data using SQL Server Integration Services.  We will review the various cleansing tools accessible from within SSIS including native Integration Services components, T-SQL, and SSIS scripting.  In addition, we'll briefly review the new SQL Server Data Quality Services and its integration with SSIS.  We'll cap off the discussion with demonstrations of several methods for data cleansing. X-ALT-DESC;FMTTYPE=text/html:

Cleaning Up Dirty Data with SSIS

Dirty data is everywhere, and it's headed for a database near you.  Extraction, transformation, and loading (ETL) can be difficult, but often the most challenging component of that process is the validation and clean up of data. Information must be cleansed in such a way that it retains its original message and business value, while conforming to the expectations of the destination system(s). 


In this session, we'll discuss some design patterns for addressing different types of dirty data using SQL Server Integration Services.  We will review the various cleansing tools accessible from within SSIS including native Integration Services components, T-SQL, and SSIS scripting.  In addition, we'll briefly review the new SQL Server Data Quality Services and its integration with SSIS.  We'll cap off the discussion with demonstrations of several methods for data cleansing.

Tim Mitchell

Tim Mitchell is a business intelligence consultant, database developer, speaker, and trainer.  He has been working with SQL Server for over 9 years, working primarily in business intelligence, ETL/SSIS, database development, and reporting.  He has earned a number of industry certifications and holds a Bachelor's Degree in Computer Science from Texas A&M at Commerce, and is a Microsoft SQL Server MVP.  Tim is a business intelligence consultant for Artis Consulting in the Dallas, Texas area.

As an active member of the community, Tim has spoken at national, regional, and local venues including the SQL PASS summit, SQL Connections, numerous SQL Saturday events, and various user groups and PASS virtual chapters.  He is a board member and speaker at the North Texas SQL Server User Group in Dallas, serves as the co-chair of the PASS BI Virtual Chapter, and is an active volunteer for PASS.  Tim is an author and forum contributor on SQLServerCentral.com and has published dozens of SQL Server training videos on SQLShare.com.

Tim is a contributing author on the charity book project MVP Deep Dives 2, and is coauthoring SSIS Design Patterns (available July 16th).

You can visit his website and blog at TimMitchell.net or follow him on Twitter at twitter.com/Tim_Mitchell.

http://www.timmitchell.net UID:SQLBITS1483SEQUENCE:0 DTSTAMP:20130523T093035Z END:VEVENT END:VCALENDAR