A practical walkthrough of migrating from a centralised data warehouse monolith to a contract-driven Data Mesh, using a fictional online toy retailer's website analytics as a concrete example. The article explains why traditional data warehouses become bottlenecks, outlines the four pillars of Data Mesh, and demonstrates how foundational and consumer data products are structured with input/output ports. Central to the transition is the Open Data Contract Standard (ODCS) by Bitol — a YAML-based, machine-readable, tool-agnostic specification covering schema, data quality, SLAs, ownership, and access. The piece also covers how standardised contracts enable interoperability with tools like dbt, Great Expectations, and Soda, and how they provide guardrails for LLMs and MCP-based autonomous agents querying organisational data.

12m read timeFrom towardsdatascience.com
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Table of contents
Why traditional data warehousing becomes a monolithWhat Data Mesh actually changes (and what it doesn’t)Data contracts: the missing stabiliserThe example: website analyticsThe centralised (pre-Mesh) approachWebsite analytics in a Data MeshWebsite User Behaviour Foundational Data ProductMarketing Lead Conversion Metrics Consumer Data ProductZooming into Data ContractsData Contracts enabling interoperabilityLLMs, MCP servers and Data Contracts
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