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Data strategy workshop Dutch Data Summit 2023

Data strategy workshop Dutch Data Summit 2023

How does your data maturity inform your data strategy? In this breakout session we explored how to let your data maturity inform your data strategy.

Avatar for Sven Stringer

Sven Stringer

April 15, 2023

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Transcript

  1. 3

  2. Common problems with strategy 1. Too much focus on data

    and tech 2. Let’s just get all the good people 6
  3. People Five pillars of Machine learning strategy 8 Create a

    clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data
  4. People Five pillars of Machine learning strategy 9 Create a

    clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data
  5. People Five pillars of Machine learning strategy 10 Create a

    clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data
  6. People Five pillars of Machine learning strategy 11 Create a

    clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data
  7. People Five pillars of Machine learning strategy 12 Create a

    clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data
  8. People Five pillars of Machine learning strategy 13 Create a

    clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data
  9. The maturity levels we distinguish 15 Data Fluent 4 3

    1 Data Literate Data Knowledgeable 2 Data Aware
  10. Identify your maturity gap 16 1: DATA AWARE 2: DATA

    KNOWLEDGEABLE 3: DATA LITERATE 4: DATA FLUENT Current: 60% Goal: 75%
  11. People Example: steps to become fully data literate 17 Create

    a clear data strategy and define KPIs Value ML Strategy Organisation Process Technology Data Create a clear data strategy and define KPIs Align personal and team goals with organisational KPIs Make your product teams (more) cross-functional to reduce team hand-overs Define and integrate responsibilities throughout the organization Standardise ways of working to include documentation, testing and peer reviews to improve quality of data products Provide a basic data platform for executing analyses and ML model development Encourage the adoption of software development best practices such as the use of version control systems Create a central data governance policy
  12. Takeaways 19 Adapt next steps to current and ideal maturity

    levels Not every organisation needs to be at the highest maturity level Think about machine learning strategy holistically