Data Products | A Guide to Data Products
Category: Data Governance | Tags: #data products, #data mesh, #data governance
Practical guide to data products: definition, rulebook, business canvas, MVDP, sharing, quality/SLO, change/deprecation and measurable value.
Many organisations do not have “too little data”. They have too little predictability: you find something in the catalogue, but do not know whether it is safe to build on, how it changes, or who responds when something breaks.
Data products are an attempt to make a few important deliverables more manageable over time, without turning the entire data platform into a governance project.
Who is this guide for?
Data engineers, analytics engineers, data scientists, BI/analytics, data governance and those who lead data teams.
The guide helps you make concrete decisions: what is a data product and what is it not, what minimum requirements are reasonable, and how do you build something that withstands change without people creating copies?
How to use this guide
Three entry points:
- Want to understand what a data product is? Start with chapters 1–2.
- Starting a data product today? Go to the 100-day plan in chapter 9.
- Working with a catalogue or portfolio? Start with chapter 6.
Chapters
- What is a data product?
- Rulebook and portfolio: product vs component, ownership and domains
- Business canvas and MVDP: from “good idea” to something people dare to use
- Value: why data products are worth the effort
- Interfaces first: sharing and data contracts
- In practice: product page, catalogue and components
- Quality and reliability: tiers, SLOs and response patterns
- Change, versioning and deprecation practices
- Product forum, 100 days as a data product owner, and Learn more
