As data assets and usage needs grow (especially with the application of AI), so do the realities of needing to better utilize data as a trusted and reusable asset. A solid Data Governance organization framed around Data Stewardship with clearly defined objectives provides the discipline and methodology to do just that. This session will explore common Data Quality challenges and their associated misconceptions. Data Stewardship is key to enabling Data Quality so the session will focus on building a Data Governance program that supports the role of the Data Steward. Participants will be left with a clearer understanding of how Data Quality, Data Stewardship, and Data Governance are key inputs into any data strategy.
What if your biggest data problems weren’t about tools at all—but about how your data is managed? In this session, the speaker cuts through the AI hype to spotlight the fundamentals: data quality, stewardship, and governance as the true foundation for reliable analytics. Through relatable examples and real-world “data chaos” scenarios, you’ll see why unclear definitions, inconsistent rules, and unmanaged data flows quietly derail even the most advanced initiatives. If you’re looking to turn messy, fragmented data into a trusted asset—and finally stop fighting the same issues over and over—this talk shows you where to start and how to make it stick.
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