Data Quality and the Single Version of the Truth
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Tom Breur
November 2009 Introduction Data quality emerges as users create value from working with data. It implies value to someone; it is not a property that is intrinsic in the data itself. When nobody uses data, it has zero value. In order to execute corporate strategy you need to know what’s going on. To make data usable, it is eminently important to construct some uniform and consistent structure that houses the data. A data warehouse (DWH). Traditionally, in data warehousing we have taken source data, and applied extract, transform, load (ETL) to clean, scrub, and move data to our data warehouse (DWH) star schemas. We don’t want “bad” data going into the DWH, because that means it would show up in corporate reports (an architectural exception would be a Data Vault). This might trigger business users to question the accuracy of the DWH, which is supposed to be the trusted source for integrated corporate data. |
