How To Select Technology For Data Mesh
summary
Positions Data Mesh as a socio-technical shift that trades centralized bottlenecks for domain teams who can onboard sources faster but must absorb distributed skills and self-service infrastructure costs. Demonstrates building a self-service platform with Thoughtworks and Saxo Bank that integrates DataHub with Great Expectations via a contributed plugin and later productizes it as agraldata.io, and warns there is no off-the-shelf mesh portal like Backstage yet. Recommends mapping high‑value data products first and staggering platform investment.
AI-written summary · about
chapters (9)
- 0:00Introduction to data mesh
- 1:51Problems with centralization
- 5:03Socio-technical trade-offs
- 6:52Defining data products
- 10:38Four pillars of data mesh
- 14:18Designing the platform
- 17:51Technology and tooling
- 22:37Integration and pragmatism
- 26:46Strategic implementation
related talks
23mHow To “Data Mesh”: What You Need To Know To Make It Real
51mData Mesh – Successful with People, Process, and Technology
52mFrom Data Mess to Data Mesh: Navigating People, Process & Platforms
20mEmbracing Data Mesh: A Modern Strategy for Scalable Data Management
38mData Mesh, Now
43mWhen design meets data: Using Data Mesh for a consumer and business-driven data strategy
34mBest and Worst Days of Data Mesh
36mIntroducing Data Mesh A Paradigm Shift In Analytical Data Management Architecture