[DSC DACH 25] Mario Meir-Huber Demystifying Data Products: From Buzzword to Practical Implementation.pptx

“Data Product” has become a buzzword in many organizations — often used without a clear understanding of what it truly means. In this session, we’ll cut through the noise. You’ll get a clear definition of Data Products, explore why they matter, and learn how to design and implement them in practice — both from a business and technical perspective. Whether you’re a data engineer, analyst, or decision-maker, this session will give you a concrete foundation for working with data products in real-world environments.

1. Demystifying Data Products From Buzzword to Practical Implementation Mario Meir-Huber

2. Agenda 1 What are (Data) Products? 2 How to define a Data Product? Key Ingredients of a Data Product 3 The Data Product flow 4 5 The business dimension

3. What are (Data) Products? 1

4. Is this a product?

5. And this?

6. And this?

7. How to define a Data Product?

8. A data product delivers value to its consumers.

9. A data product delivers value to its consumers. There is no value without Quality

10. A data product delivers value to its consumers. There is no value without Quality There is no value without ROI

11. A data product delivers value to its consumers. There is no value without Quality There is no value without ROI There is no value without reliability

12. A data product delivers value to its consumers. There is no value without Quality There is no value without ROI There is no value without reliability There is no value without usability

13. A data product delivers value to its consumers. There is no value without Quality There is no value without ROI There is no value without reliability There is no value without usability There is no value without interoperability

14. A data product delivers value to its consumers. There is no value without Quality There is no value without ROI There is no value without reliability There is no value without usability There is no value without interoperability There is no value without impact

15. A data product delivers value to its consumers. There is no value without Quality There is no value without ROI There is no value without reliability There is no value without usability There is no value without interoperability There is no value without impact

16. Key Ingredients of a Data Product 3

17. The GAP Governance Architecture People

18. The GAP Governance Architecture People

19. The GAP Governance Architecture People

20. The GAP Governance Architecture People

21. Types of Data Products End user view System view Source aligned Data Products Consumer aligned Data Products Aggregated Data Products

22. The Data Product flow 4

23. Data is always in motion Premise 1

24. Business requirements change frequently Premise 2

25. Upstream changes impact downstream data processing Premise 3

26. Data is always in motion Data Retrieval Data Integration Value Extraction Continuous Improvement Continuous Adaption G A P

27. Data Retrieval Data Integration Value Extraction

28. Data Retrieval Data Integration Value Extraction

29. Data Retrieval Data Integration Value Extraction

30. The business dimension 5

31. Technical Feasibility Impact High Low High Low Low hanging fruits Challengers Playgrounds Underworld

32. Technical Feasibility Impact High Low High Low Data Product B Data Product A Data Product C Data Product D Data Product E Data Product F Data Product G

33. Technical Feasibility Impact High Low High Low Data Product B Data Product A Data Product C Data Product D Data Product E Data Product F Data Product G

34. Creating a strategic roadmap Scoring the value per Data Product Scoring the technical feasability to implement Calculate the value when removing blockers Step 1: ROI calculation (Revenues – Investment costs) / Investment costs

35. Creating a strategic roadmap Scoring the value per Data Product Scoring the technical feasability to implement Calculate the value when removing blockers Step 1: ROI calculation (Revenues – Investment costs) / Investment costs Step 2: Break-even calculation: Σ (Revenues per Year) – (Fixed cost + Σ (Variable Costs per Year)) >= 0

36. Creating a strategic roadmap Scoring the value per Data Product Scoring the technical feasability to implement Calculate the value when removing blockers "The new Data Product will break even within three years and generate a 51% return on investment over the first four years with profitability accelerating beyond that point."

37. Creating a strategic roadmap Scoring the value per Data Product Scoring the technical feasability to implement Calculate the value when removing blockers Step 1: measuring fixed parameters along the GAP-dimensions (e.g. Data Governance maturity)

38. Creating a strategic roadmap Scoring the value per Data Product Scoring the technical feasability to implement Calculate the value when removing blockers Step 1: measuring fixed parameters along the GAP-dimensions (e.g. Data Governance maturity) Step 2: measuring variable parameters per Data Products

39. Creating a strategic roadmap Scoring the value per Data Product Scoring the technical feasability to implement Calculate the value when removing blockers Focus on easy to resolve blockers . e.g. I nvestment into Data Governance by 1.5 million will unlock 15 million in business value over the next 5 years

40. Failing to invest in Data might lead to this …

41. Linkedin : Mario Meir-Huber Let’s stay in touch!