Modern Data Architecture: Breaking the Big Data Monolith
summary
Argues that the centralized data lake creates organizational and technical bottlenecks and proposes Data Mesh as a practical fix with four specific principles: domain ownership, data as a product, self-service platform, and federated governance. Recommends cloud tooling (AWS/Azure/GCP storage, catalogs, IAM, automated pipelines), cites a Proofpoint pilot that exposes one dataset as a product to build a customer dashboard, notes the second product takes less time, and predicts adoption over the next 5–7 years.
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chapters (12)
- 0:00Introduction and setup
- 1:11From monoliths to microservices
- 7:57Big Data monolith limitations
- 17:27Introducing data mesh
- 23:04Domain ownership in practice
- 27:19Data as a product
- 30:07Self-service data platform
- 32:56Federated governance
- 35:02Building a data mesh
- 40:15Hype cycle and future trends
- 43:06Implementation lessons
- 45:12Future of data architecture
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