M

Metadata

Data that describes other data, providing context about structure, meaning, origin, and usage.

In-Depth Explanation

Metadata is "data about data" - information that describes characteristics of other data. It helps users and systems understand, find, and use data effectively.

Types of metadata:

  • Technical: Schema, data types, constraints
  • Operational: Created date, last updated, row counts
  • Business: Definitions, ownership, classifications
  • Social: Ratings, comments, usage frequency

Metadata examples:

  • Column names and data types
  • Table descriptions and purposes
  • Data owner and steward
  • Data quality scores
  • Access permissions
  • Transformation logic

Metadata management:

  • Data catalogs (central repository)
  • Metadata standards (naming conventions)
  • Automated collection
  • Manual curation for business context
  • Search and discovery

Why metadata matters:

  • Find relevant data (discovery)
  • Understand data meaning (context)
  • Ensure proper use (governance)
  • Assess data quality (trust)

Business Context

Good metadata makes data findable and usable. Without it, data becomes a liability rather than an asset.

How Clever Ops Uses This

We help Australian businesses implement metadata management, making data assets discoverable and trustworthy for AI applications.

Example Use Case

"A data catalog with metadata showing: table purpose, column definitions, data owner, update frequency, and quality score - helping analysts find and trust data."

Frequently Asked Questions

Category

data analytics

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