What is a Data Mesh - And How Not To Mesh it Up
summary
Defines Data Mesh as domain-owned data plus global governance and gives concrete rollout steps: use a self-serve data platform, assign ownership via a RACI, and set data reliability SLAs/SLOs/SLIs. Describes Monte Carlo’s Data Observability product and five pillars—freshness, field-level distribution, volume, schema, lineage—and borrows devops practices (New Relic/Datadog/PagerDuty analogies). Claims data engineering is “6–10 years behind” software, cites orgs with hundreds of thousands of tables and examples of tables going months stale.
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chapters (15)
- 0:00Intro
- 2:43Data Mesh
- 8:07Data Mesh Principles
- 10:27Considerations
- 16:24Devops
- 24:27Data Freshness
- 25:55Distribution
- 26:55Volume
- 27:44Schema
- 28:41Lineage
- 31:02DomainDriven Accountability
- 32:29SelfService
- 34:36Data Reliability SLA
- 36:22Key Assets
- 38:32Data Reliability Lifecycle
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