Summary
Data quality efforts conducted by enterprise architecture (EA) professionals used to be all about "cleaning the data." EA pros incorporated increasingly sophisticated transformation rules into data integration processes and purchased data quality tools to further validate, correct, enrich, and de-duplicate. Many in technology management have even called the war on data quality won — in the data warehouse. However, data quality is more than just cleaning data in the warehouse or in any other system of record, such as an application database. Business stakeholders and analysts are shopping and blending data across internal and external data sources and asking questions of the data that they have never asked before. This is exposing many more issues, complexities, and dependencies with the data. This report helps EA pros transition to data quality efforts that create personalized, relevant, and trusted data rather than just clean data.
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