For the past few years, master data management (MDM) has been a hot topic among enterprise architects and data management professionals. But many of these evangelists have felt like rebels without a cause because their MDM initiatives have been primarily IT driven with minimal business sponsorship and participation. In other words, the business expects high quality data, but hasn’t taken much accountability in delivering it. 

Data quality (DQ) management, a more mature technology and competency than MDM - and a required core capability for any MDM solution - has also struggled to be embraced by the business as a top priority.  More often than not, DQ has been relegated as a supporting downstream batch application for ETL, data warehousing and business intelligence applications, but not for a broader cross-enterprise data architecture including upstream transactional systems and processes.

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