Data Quality Issues Leave Everyone Holding the Bag

Bookmark and Share

By Todd Schraml

Quality can be a hard thing to define. What is good and what is bad may not be easily identified and quantified.  When a data mart accurately reflects data exactly as found in the source, should that be considered a quality result? If the source data is bad, is the data mart of high quality or not? If the data mart differs from the source, when is the difference an improvement of quality and when is said difference evidence of diminished quality? While it may seem self-evident that correcting the source of load data would be the "right" thing to do, in practice that direction is not necessarily self-evident ... read on.

To stay on top of all the trends, subscribe to Database Trends and Applications magazine.