Mark Brady, Deputy Chief Data Officer for TRMC at KBR joins the show today to hone in on data knowledge and management best practices. With an extensive background in mathematics and computer science and experience in various industries, Mark discusses the essential elements of effective data management. He critiques common data science practices, such as the flawed concept of the data life cycle and the misuse of terms like 'data lake.' Mark emphasizes the need for rigorous, structured approaches and outlines the four levels of knowing in data science. He also introduces the notion of next-generation data management and models like the Active User Model and the Notified User Model. This episode is packed with insights on how organizations can improve their data practices to make better, more informed decisions.
Key Takeaways:
- Adopt Next Generation Data Management Principles: Focus on structured, well-defined data management practices rather than relying on buzzwords like "data lakes." Ensure your data is integrated and not siloed to avoid "data swamps."
- Emphasize Data Structure: Use structured data models to enable automation and ensure accurate and consistent data processing and analysis.
- Understand the Four Levels of Knowing: Having the data, knowing what data you have, understanding the data, understanding the data in the context of other data.
- Clarify Terminology: Make sure everyone involved has a common understanding of key data management terms like "data lake," "data warehouse," and "data mesh." This avoids confusion and ensures everyone is on the same page.
- Focus on Rigor and Precision: Adopt a rigorous and precise approach to your data practices. This will lead to more reliable outcomes and better decision-making capabilities.
Quote of the Show:
- “ It turns out that we don't actually manage data in a data life cycle, nor should we manage in a life cycle.” - Mark Brady
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