Serving Data as API
summary
Argues that a virtual layer exposes heterogeneous sources as data virtualization APIs, using API gateways, SQL endpoints, caching, data catalogs and engines like Spark to deliver consistent, reliable, high‑velocity responses. Claims this creates data as a product: domain teams publish curated datasets, federated governance maps security, and a single plane of glass removes central‑team bottlenecks. Recommends starting with an MVP/POC or greenfield API, not a full rip‑and‑replace, and reports that the approach reduces fragmentation and integration complexity.
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chapters (11)
- 0:00Intro
- 0:45Introduction
- 2:26Why API
- 4:48Challenges
- 6:36Data Source
- 8:05Data Virtualization
- 13:39Data Match
- 16:51Data Ownership
- 19:26Example
- 21:04Wrap Up
- 21:37Questions
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