Learn OpenMetadata by building it.
In most organisations, nobody knows where the data is, who owns it, or whether it can be trusted. A data catalog fixes that. In this module you'll deploy one from scratch, ingest a real database, and lay the first bricks of governance — entirely hands-on.
Why a data catalog?
Ungoverned data is the silent tax on every analytics and AI effort: duplicated datasets, no agreed source of truth, no owner to ask, numbers nobody trusts. A data catalog is where an organisation makes its data findable, understandable and accountable — the practical entry point to data governance. This module is the hands-on half; the conclusion places it in the DAMA-DMBOK framework and shows where the tool stops and organisation begins.
A catalog only earns trust if it's maintained by people with clear roles — not just installed. Throughout, watch for the governance reasoning behind each step, not only the clicks.
By the end, you'll be able to…
- Explain what a data catalog is and where it sits in a governance approach.
- Deploy OpenMetadata locally with Docker Compose.
- Connect and ingest a first data source.
- Explore assets — schemas, lineage and profiling.
- Lay the first governance bricks: business glossary, classification, ownership.
What you'll learn
The metadata model
Entities, services, schemas and FQNs — the skeleton everything else hangs off.
Lineage that means something
Table vs column lineage, how it's auto-derived, and why it's the governance backbone.
Governance in layers
Glossary, classification, ownership, data quality — and how a data contract binds them.
The API surface
Everything is reachable by REST API — the basis for automation, CI checks, and integrations.
The path
Get OpenMetadata running
The container stack explained, then up and running on your machine.
Catalog & Ingestion
Entities, services and FQNs — then run your first real ingestion.
Lineage
Table and column lineage — derived automatically, drawn by hand, asserted by API.
Governance & Data Contracts
Glossary, tags, ownership, quality — and binding them into an enforceable contract.
Conclusion — DMBOK lens & verdict
Map it all to DAMA-DMBOK, weigh the pros & cons, and see where the tool stops and organisation begins.
Every lesson has Do this exercises — actually click and type in your own instance. The understanding comes from the doing, not the reading. Your progress and checked-off steps are saved in this browser.
This is Module 1 — OpenMetadata. It ends with a working catalog, an ingested source, a starter glossary and a classified, owned asset. Next in the series: Data Contracts with ODCS on top of OpenMetadata, then data quality & observability — each module builds on this one.
Official documentation: docs.open-metadata.org