Data Governance is seeing an inflection point as AI presents unique opportunities to automate mundane tasks like data documentation, manual tagging, etc. Despite the opportunities, many leaders still report that data governance is hard. So curious, how is Data Governance changing for most strategic data management leaders? I'd love to hear from peers if anyone has been able to get measurable ROI from doing data governance, not just productivity gains like finding data more easily.

Data GovernanceData & Analytics
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Chief Data Officer in Software21 days ago

Hey Kash!  While I was an analyst I spoke with literally thousands of data leaders - and my #1 recommendation, without question, was 'find a way to quantify the business value of your efforts'.  We know this is the best way to ensure a continued focus on governance, to secure data stewardship support, to continue to receive funding, and on, and on.  Yet, even though I recommended this hundreds and hundreds of times, I can count on one hand the number of data leaders who actually followed my advice.  Amazingly, many still believe that quantifying the value governance is impossible - which is a complete myth.  

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no title16 days ago

Well said, Malcolm!! My upvote for you, couldn’t agree more. Being able to demonstrate ROI requires some thought and a framework to capture those quick wins. Often, these are communicated via slides but quickly forgotten. It’s almost like building your “quick win catalog” to list everything data governance brings to the organization, whether related to revenue, cost, or risk.<br><br>I’m hopeful that AI can change this. There’s an opportunity to automate data enrichment (probably through machine learning), making it easier to classify and tag data, suggest meaningful definitions, or provide business context based on semantics.<br><br>I’m curious if any peers here have made progress in capturing this type of value.

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