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DTSTAMP:20260511T180251Z
DESCRIPTION:Click for Latest Location Information: http://dgiq2022east.data
 versity.net/sessionPop.cfm?confid=151&proposalid=13954\nThe health and well
 -being of business intelligence assets once in production require a level o
 f diligence, communication, and skill to mitigate adverse data events and m
 aintain a high degree of confidence. This means creating the pathway at the
  consumption layer to report and react to data events quickly. \nOrgan
 izations are also recognizing the need to practically mitigate data at its 
 ingestion to ensure accuracy through the pipeline and remediate events befo
 re they impact any assets and decisions.  \nLeverage all levels o
 f DQ to create a robust data quality strategy by:  \n\n
 Diligently bring the assets in production into good health with reactive da
 ta quality.\n
 Proactive DQ to find and report back to the business as close to the source
  as often as possible data anomalies so they can be researched and repaired
  at their source before causing havoc on the pipeline.\n
 Determining when field-level DQ is a worthwhile and effective endeavor.\n\n
DTSTART:20221206T111500
SUMMARY:Data Quality Proactive and Reactive Possibilities, Process, and Ins
 ights
DTEND:20221206T115959
LOCATION: See Description
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