Session description
Ten years ago, I began advocating for DataOps, a framework designed to improve collaboration, efficiency, and agility in data management. The industry was still grappling with fragmented workflows, slow delivery cycles, and a disconnect between data teams and business needs. Fast forward to today, and the landscape has transformed, but have we truly embraced the future of working with data at scale? This session will reflect on the evolution of DataOps, examining what’s changed, what challenges persist, and where we’re headed next.
Key Takeaways:
✅ The biggest wins and struggle in implementing DataOps over the last decade.
✅ Practical strategies for improving automation, governance, and data quality in modern workflows.
✅ How emerging trends like AI-driven automation and real-time analytics are reshaping the way we approach data management.
✅ Actionable insights on how data teams can stay agile and align better with business objectives.
Why Attend?
If you’re a data professional, architect, or leader striving for operational excellence, this talk will equip you with the knowledge to future-proof your data strategies. Whether you’ve adopted DataOps or are still figuring out where to begin, we’ll explore the lessons learned over the last decade and the innovations shaping the next one.