Getting Your Data Ready for Next-Level Uses
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The Soft Side of Data Quality
Dale: If you can't convince people that the data quality is important to their job, we're probably not going to have a long-term data quality strategy. He says it's super important to address soft issues such as validation checks on front end of care and making sure there are no further errors or mistakes made. Dale: Data quality equals completeness times validity; I'm building out a tool at IMO so that we can quickly profile data quality in clients' data set.
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