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Enabling High Quality Analytics through a Data Validity Dimension
July 2007
Pete Stiglich

In the course of my consulting work, I had the opportunity to participate in an Enterprise Data Warehouse project for a state court system, where the project team encountered poor data quality in the source systems. The OLTP application did not strictly enforce referential integrity, and there was very little in the way of attribute level constraints in the application or the database.

Of course, one should never be surprised when there is poor data quality in the source systems — experience has shown that poor data quality is the norm rather than the exception. In fact, The Data Warehouse Institute (TDWI) estimates that over $600 billion a year is lost due to poor data quality.