The document discusses common data quality problems that occur in data warehousing systems and how to check for them. It describes 11 common problem types like referential issues, data type issues, and data content issues. It recommends implementing automated checks that regularly run across source systems, staging areas, and the data warehouse. Additional profiling checks run manually include checking for outliers, minimums and maximums, sequential keys, and data types. Continuous monitoring and prevention is key to ensuring high quality data.
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ETIS09 - Data Quality: Common Problems & Checks - Presentation
1. Data Management & Warehousing
Data Quality:
Common Problems & Checks
Date: 24 April 2009
Location: Zagreb, Croatia
David M. Walker
davidw@datamgmt.com
+44 (0) 7050 028 911 - http://www.datamgmt.com
28. Data Management & Warehousing
Data Quality:
Common Problems & Checks
Thank You
David M. Walker
davidw@datamgmt.com
+44 (0) 7050 028 911 - http://www.datamgmt.com