Optimizing data discovery & DQ rule enforcement with semantics & data concepts management

@joshua.zatulove asks -
Is there any synchronization between data concepts in DQ and Data Concepts that may have been defined in Data Governance?

“It was smart enough to figure out the EIN was invalid” - are we saying the manual rules and respective regex are going to be automatically created?

@jeffery.edwards.collibra.com asks -
When can we expect this additional DQ capability (version) to be rolled out to our DQ demo and assessment environments?

@vasiliki.nikolopoulou.collibra.com asks - When would the terminology or nomenclature (such as data concepts, semantics, data classes, data categories) be aligned with the descriptions in DG?

@adam.blalock asks - What is the positioning of this functionality alongside Collibra Catalog Auto Classification? Is there overlap, or are these different enough from each other that it makes sense to use both? @kirk.haslbeck.collibra.com Do you want to respond to Adam’s question?

My understanding is - On the messaging/positioning side, we can make it more clear via distinguishing use cases. Catalog focuses on data discovery and policy enforcement (whenever ready) use case from a data steward perspective. DQ focuses on data discovery and DQ rule enforcement from a data quality analyst/engineer perspective. But, once Collibra DQ is integrated within CDIC…we need to deprecate any duplicate capabilities.