The evolution of metadata management frameworks

Julian Thomas, Principal Consultant at PBT Group

If you have worked with enterprise data for any length of time, you will know that metadata has never been a “nice to have.” Long before anyone coined phrases like data fabric or data mesh, organisations were already wrestling with the same question: how do we describe, structure, and govern the information that runs through the business?

Over the past three decades, a lot has changed, not only the tools, but also our expectations. We have shifted from static documentation to far more dynamic, interconnected frameworks. Understanding that journey helps explain where we are now, and why metadata still sits at the centre of any serious data strategy.

When metadata lived in people’s heads

In the 1990s, metadata management was mostly a manual exercise. You would find business definitions in Word documents, lineage in Visio diagrams, and critical knowledge stored in the minds of a few people who had “been around long enough.” It worked. Well, until those people left.

Central glossaries existed, but they were often incomplete, out of date, or only maintained during big projects. Lineage was drawn rather than traced. Useful, yes, but also fragile.

The big-vendor era

By the early 2000s, it became obvious that organisations needed more structure. Large vendors began offering governance and metadata capability inside broader data-warehouse and integration platforms.

These tools put discipline around glossary management, stewardship, lineage, and policy enforcement. It was progress, but it came with heavy implementation cycles and price tags that put them out of reach for many organisations. Metadata moved forward, though it still tended to sit inside IT.

Pure-play specialists take it further

A second wave followed, driven by companies that focused specifically on mastering metadata and reference data.

A good example was Orchestra Networks, whose EBX5 platform featured in the Gartner Magic Quadrant many times. They did not try to be all things to all people. Instead, they specialised and did it well. EBX5 gave organisations a strong, dedicated capability rather than a bolt-on catalogue embedded in a bigger suite. Orchestra Networks was acquired by TIBCO in 2018, a sign of how valuable and mature that specialisation had become.

These tools generally offered stronger modelling, deeper reference-data workflows, and more structured stewardship approaches. Still centralised, but more connected to the business than before.

The cloud changes the expectations

Cloud platforms shifted reality again. Pipelines and platforms were moving faster, and teams wanted metadata to keep up. A static catalogue was no longer enough.

Automation started to matter more:

• Updating lineage automatically.
• Synchronising metadata across systems.
• Embedding stewardship closer to the flow of data.

Instead of forcing everything into a single giant repository, frameworks began to acknowledge that metadata lives in many places. The goal became linking it, not relocating it.

This era also pushed business teams into the conversation. Meaning, ownership, and context were no longer only IT concerns. Instead, they belonged to the domain.

Open-source catches up

In recent years, open-source tooling has begun playing a bigger role. Cloud and (now) GenAI have lowered the barrier to what these tools can do.

One example is Open Metadata, a project that shows how far the community has come. It delivers cataloguing, lineage, and governance in a way that is accessible for organisations that want to start small and scale, without immediately jumping into a heavy proprietary suite.

Open-source platforms do not replace a framework, but they provide flexible building blocks. These are helpful for teams ready to grow capability over time.

What the journey tells us

For all the change, the intention has stayed remarkably consistent. It is still about helping organisations understand and trust their data so they can use it well.

What has shifted is the how:

• From documents → active, integrated catalogues.
• From central control → shared stewardship.
• From static maps → automated lineage.
• From IT ownership → domain + IT collaboration.

The pace of change is not slowing. Data spreads across cloud platforms, line-of-business tools, APIs, and external sources. Frameworks have to keep up.

Today, successful metadata management is less about one central repository and more about building a coherent approach that acknowledges complexity, distributes ownership, and keeps the organisation aligned.

In my next article, I will explore where we are now—including GenAI’s influence on metadata—and where frameworks are likely to head next.