How to Build Intelligent Data Strategy to Accelerate Data and AI Innovation – Mercedes Pantoja, E.ON

The importance of developing a cohesive approach that aligns with business goals, by prioritizing data quality, integration and governance to unlock the full potential of AI and data driven initiatives.
Data Innovation Summit 2024 Data Innovation Summit 2024
Data Innovation Summit 2024

Session Outline

Presentation on data strategy at the Data Innovation Summit 2024! This presentation by Mercedes Pantoja from E.ON, covers the importance of developing a cohesive approach that aligns with business goals. By prioritizing data quality, integration and governance to unlock the full potential of AI and data driven initiatives.

Key Takeaways

  • Business Alignment. Aligning your data strategy with your organization’s business objectives. To ensure that data and AI initiatives directly contribute to your goals.
  • Data Quality and Governance. Significance of data quality, integrity, and robust governance frameworks. Foundational elements for enabling successful AI innovation, as they underpin data reliability and trust.
  • Integration and Interoperability. Seamless data integration and interoperability across various systems and sources to ensure a comprehensive and holistic view of your data, which is essential for effective AI applications.
  • Continuous Learning and Adaptation. Flexible and adaptable data strategy that evolves alongside technological advancements and changing business requirements to stay ahead in the data and AI innovation landscape.
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