**Estimated reading time:** 10–12 minutes

## Definition

A **Data Catalog** is a searchable inventory of an organization's data assets and their [[Metadata]].

It helps people discover what data exists, what it means, where it comes from, who owns it, and whether it is trusted.

## Simple Mental Model

> **A Data Catalog is Google for your organization's data.**

## How It Works

A Data Catalog may inventory:

- Databases
- Tables
- Columns
- Files
- Dashboards
- Reports
- Metrics
- Models
- Pipelines
- APIs

An entry might show owner, status, description, grain, source, refresh, quality, and downstream use.

## Example

Search:

`Revenue`

Results:

```text
Net Advertising Revenue [Certified]
Subscription Revenue [Certified]
Gross Advertising Revenue
Revenue Forecast [Restricted]
```

Each result includes an owner and business definition.

## How It Fits Into the Bigger Picture

```text
[[Metadata]]
     ↓
Collected and organized in
     ↓
[[Data Catalog]]
     ↓
Datasets + Metrics + Reports + Owners
```

The catalog may surface [[Data Lineage]], [[Data Quality]], [[Business Glossary]], [[Data Owner]], and [[Data Steward]] information.

## My Company / Real-World Context

A new employee should be able to search `Video Completion Rate` and see its definition, owner, dataset, source system, refresh, and dashboards that use it.

## CTO Perspective

Buying a catalog tool does not create governance. A catalog full of stale descriptions is only expensive documentation.

The hard part is the operating model: who maintains it, who certifies assets, what "trusted" means, and how deprecation works.

### Questions to Ask

- Can employees discover trusted data without knowing who created it?
- How do we mark certified vs experimental datasets?
- Who maintains catalog entries?
- Does the catalog show [[Data Lineage]]?
- Does it expose [[Data Quality]] status?
- Are people actually using it?

## Meeting Scenario

**Situation:** Someone proposes an expensive enterprise Data Catalog because "every mature organization needs one."

**Possible response:**

> "Before selecting a platform, let's define the problem. Are we struggling with discoverability, ownership, duplicated datasets, lineage, business definitions, or all of these? Then we can determine the lightest solution that meets the need."

## Key Takeaways

- A Data Catalog is a searchable inventory of data assets and metadata.
- It supports discoverability, self-service, and governance.
- A tool alone does not create governance.
- Operating model and adoption matter more than the interface.

## Related Concepts

- [[Metadata]]
- [[Data Governance]]
- [[Data Lineage]]
- [[Data Quality]]
- [[Business Glossary]]
- [[Data Owner]]
- [[Data Steward]]