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Definition
Metadata is data that describes other data.
It provides context needed to understand, discover, govern, and operate datasets.
Simple Mental Model
Data is the book. Metadata is the title, author, table of contents, publication date, and description on the back.
How It Works
Metadata can be grouped into several categories.
Technical Metadata
Table names, columns, data types, keys, schemas.
Business Metadata
Business definitions, owners, descriptions, certified use.
Operational Metadata
Refresh time, pipeline duration, row counts, success/failure.
Governance Metadata
Owner, steward, classification, retention, access rules.
Example
Without metadata:
tbl_vw_agg_final_v2
dt
uid
cnt
sec
src
With metadata:
Name: Daily Viewing Aggregate
Purpose: Daily content consumption reporting
Source: JW Player viewing events
Grain: One row per user/content/day
Owner: Audience team
Refresh: Daily 05:00
sec: Total valid watch seconds
How It Fits Into the Bigger Picture
Data Lineage uses metadata to understand relationships.
Data Governance uses metadata to record ownership and classification.
Data Quality uses metadata to record rules and results.
Data Catalog makes metadata searchable.
My Company / Real-World Context
Useful metadata could identify which audience dataset is certified, who owns it, how often it refreshes, and which source systems feed it.
CTO Perspective
A mature organization moves knowledge from:
People's heads
↓
Documented metadata
↓
Searchable organizational knowledge
The useful question is:
Is the metadata complete, current, discoverable, and actually used?
Questions to Ask
- Who owns this dataset?
- What business purpose does it serve?
- What is its Grain?
- Where does it come from?
- How often is it refreshed?
- Is it certified for business use?
- Can users discover this information without asking the original developer?
Meeting Scenario
Situation: A new analyst finds four datasets that appear to contain audience information.
Possible response:
"If the only way to know which dataset is trusted is tribal knowledge, that's a scalability problem. Let's make the owner, purpose, status, grain, source, and refresh information discoverable as metadata."
Key Takeaways
- Metadata is data about data.
- Technical metadata explains structure.
- Business metadata explains meaning.
- Operational metadata explains processing and freshness.
- Governance metadata explains ownership and controls.
- Data Catalog makes metadata discoverable.
Related Concepts
- Data Catalog
- Data Governance
- Data Lineage
- Data Quality
- Business Glossary
- Data Owner
- Data Steward
- Grain