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DTSTAMP:20260514T080050Z
DESCRIPTION:Click for Latest Location Information: http://edw2021.dataversi
 ty.net/sessionPop.cfm?confid=133&proposalid=12654\nThere is increasing awar
 eness in the data management space that data quality is fundamental to bein
 g able to generate insight from data. For those of us who worked in an
 alytics before it was cool, we grew up with the concept of GIGO (garbage in
 , garbage out), which is still relevant today. Builder analogies show 
 the result of a poor foundation. Without data quality at the raw data 
 level, there cannot be information quality at the analytical level.\nRealiz
 ing the importance of data quality and understanding that metadata can be u
 sed to identify data quality issues such as elements inconsistent with defi
 nitions, we move beyond the first step. How can the metadata lifecycle
  (Identify, Define, Review, Publish, Update) be used to support data valida
 tion? Business rules for data validation can be derived from metadata 
 and reference data. Metadata can play an integral role as a continuous
  process for data quality improvement. \nWhat will be shared:\n\n
 Metadata lifecycle\n	Metadata for data validation\n
 Continuous process for improvement of data quality\n
 Lessons learned at IRS-RAAS-DMD\n\n
DTSTART:20210422T134000
SUMMARY:Improving Data Quality: Metadata as a Continuous Process
DTEND:20210422T142959
LOCATION: See Description
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