Stop treating data governance as a "data cop" function and start using it as a high ROI offensive weapon. In this episode, Peter Kapur, Head of Data Governance and Data Quality at CarMax, breaks down how to move beyond defensive compliance to drive profitability, customer experience, and better data science outcomes.Critical Insights for LeadersShift from defense to offense Data defense covers the mandatory regulatory and legal requirements like privacy and cybersecurity. Data offense involves everything else that hits your bottom line, such as investing in data quality to save or make money.Prioritize problems over frameworks Avoid bringing rigid policies and "data geek" terminology to business leaders. Instead, spend time listening to their specific data struggles and apply governance capabilities as solutions to those problems.Data quality makes governance tangible Without high quality data, governance is just a collection of abstract policies. Improving data quality empowers data scientists to produce better models and gives analytics teams the ability to discover and trust their data.Key Moments in the Conversation02:41 Defining the clear line between defensive regulation and offensive growth 06:03 Why data quality and data governance must sit together to be effective 11:00 Shifting from "data school" to "business school" to communicate value 13:12 Quantifying the ROI of data governance through customer wins and time savings 18:35 Actionable advice for starting an offensive strategy from scratch Wisdom from the Episode"If we meet the laws, we meet the regulations, we meet the legal, how do we leverage our data? It is a mindset shift versus, let me lock my data down, no one use it." Tactical Advice for ImplementationEnsure adoption through personalization Design tools and processes that are personalized to specific roles so they feel like a natural part of the workflow rather than a burden.Focus on the eye of the consumer Treat every person in the organization as a "data citizen" and remember that data quality is ultimately defined by the needs of the people consuming it.Join the ConversationSubscribe to the podcast on your favorite platform to catch every episode. Follow us on LinkedIn to stay updated on the latest trends in data leadership.

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