Data Management as the Foundation of AI: From Data Lake to Data Product & Data Mesh – Real-World Insights
Success Factors & Skills for Effective Strategic Data and AI Management – Based on Real-World Experience
Effective strategic data and AI management is the discipline that treats data not merely as a byproduct of IT, but as a business asset. Strategic data and AI management ensures that data and artificial intelligence are not used in isolation, but rather systematically and holistically as key drivers of business success. It serves as the bridge between business strategy and technological implementation.
What are the key concepts, and what can actually be implemented in practice?
Featured Topics:
- Data productsare self-contained, usable units consisting of data, code, metadata, and infrastructure that can be accessed via standardized interfaces.
- Data lakehouse(e.g., Databricks or Snowflake), which combines the structure of a data warehouse with the cost-effective storage of a data lake.
- Data Mesh, defined as the totality of these interconnected products.
- Federated Computational Governancewith Data Product Owners, Data Product Developers, Data Platform Engineers, and a Federated Governance Council? Or would a model that’s more robust for mid-sized companies and large corporations be preferable to the “pure” Data Mesh role model?
- More—or something else?
In this interactive format, Inge Hanschke and Tania Schmid share insights drawn directly from their many years of professional experience
Format:
- Short, practical insights from Inge Hanschke (approx. 10 minutes each)
- This will be followed by an open discussion and exchange of experiences. What are your thoughts?
If you want to play an active role in shaping digital and AI transformation, you should be there.
We look forward to hearing from you!