This session provides a forum for discussion of fundamental principles that make complex data more understandable, usable, and accessible so that station leaders can more effectively communicate performance gaps and make better informed decisions for the organization. A framework, currently in use at one organization, will provide the basis of a discussion on key attributes to support a deliberate, step-by-step approach that helps measure what matters in a more efficient and more engaging manner. The intent of this session is to lay the foundation for future work on exploring the value of using AI/Machine Learning to improve data analytics and visualization.

Participants

  • Kimbel Leffew (CNS Pantex)
  • Brian Andrews (CNS Y-12)
  • Ashley Massucci (CNS Pantex)
  • Kristin Zastrow (Xcel Energy)

Session Recording

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Resources

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Session Notes

Discussion

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