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What makes business data trustworthy, and why does it matter for AI? Data quality, clear ownership, consistent definitions, and an understanding of where information comes from help organizations make better decisions and build a stronger foundation for AI. In this episode of the Orlando Insights Podcast, host Henry Orlando Clavo welcomes Olga Maydanchik to explore data quality, data governance, and AI readiness through practical lessons from enterprise data management. Olga is a practitioner, consultant, and educator with more than 25 years of experience. Her career includes roles at Citi, AIG, Deutsche Bank, Voya Financial, Walmart, and Anywhere Real Estate. She also contributed to the Data Management Capability Model (DCAM) and co-authored the Data Quality for Practitioners educational program. Questions we explore: • What makes data trustworthy enough for business decisions? • How does poor data quality affect business performance? • Who should own data quality and resolve conflicting reports? • What are data contracts, and how do they establish accountability? • How do metadata and data lineage help teams understand their data? • What should businesses assess before launching an AI initiative? Whether you’re a business leader, data engineer, analyst, or governance professional, this conversation explores how to connect better data practices to meaningful business outcomes. Subscribe to the Orlando Insights Podcast for conversations on technology, business, and leadership. What’s your organization’s biggest data challenge? Share it in the comments. #DataQuality #DataGovernance #OrlandoInsightsPodcast

Join us in this episode where Laurent Dressie, Chief Evangelist of Data Governance Kitchen, shares expert insights on data governance and AI governance. Learn practical approaches, common challenges, and emerging trends in managing data as a product, empowering organizations to build value through strategic data practices.