Metadata - An Introduction


What is Metadata?


Metadata in most simple terms means “structured data about data” or “data that describes something (that may or may not itself be data).” The prefix “meta” comes from the Greek and can indicate change, as in metamorphosis; or it can mean beyond or after, as in metaphysics. In information technology usage, the word metadata has come to be used as a definition or description of data: a small indicator that encompasses and points to a larger piece of information. The library card catalog is the standard metaphor for metadata: each card represented and led the user to a much larger body of information, the book or other item cataloged. Data is a valuable corporate asset, which outlasts applications and processes. Analysis of data allows organizations to learn and grow.

The word metadata was first recorded in the dictionary in the 1980s, but metadata has been used since the 1960s when the first software programs were written.

Why do we need to describe things?

  • Discover: to find out that things exist
  • Locate: to find out where things are
  • Request: to ask for something
  • Access: to get something – so we can use it


Metadata helps us understand data, including definitions of what it is, how it is used, who owns it, and data quality. Metadata describes the processes and tools that maintain and act on that data. So metadata goes beyond the traditional data dictionary or card catalog, and can describe the entire environment, which we have built to collect, maintain, and deploy our data assets.


Why do we need metadata?

  • To ensure proper documentation and preserve critical information
  • To help you publicize and support the data or your organization
  • So you won’t forget how you collected and processed your own data
  • So information is not lost when an employee leaves
  • So the data can be used again in the future
  • So you can tell if you need other people’s data — and how to use it
  • To help your organization share data in a consistent way without duplication
  • To preserve the value of the data over time
  • To expedite the learning curve for new employees to understand the organization’s data


Some sources for metadata in an organization:

  • Conceptual, Logical, and Physical Data Models
  • Business Definitions
  • Business Processes
  • Technical Definitions
  • Business Rules
  • Transformation Rules
  • Attribute Characteristics – field type, field size, etc.
  • Data Source System(s)
  • Data Creator
  • Data Purpose
  • Data Quality Rules
  • Data Quality Issues and more



Metadata has broad applicability across the enterprise. There is virtually no process in the entire IT organization that can’t benefit from metadata. In the next article we will provide a deep dive into the types and sources of metadata.

References & Bibliography

Milstead, Jessica and Susan Feldman – “Metadata: Cataloging by any other name …” in Online, Jan/Feb 1999, p24–31. A very lucid description of what metadata is and does, what the term means, and what the challenges are in implementing metadata schemes.

D Gleason – “An Evolutionary Approach to Metadata Management”

About the Author

Manish Malhotra is an expert in the fields of data warehousing, business intelligence, and metadata. His expertise includes enterprise information management, technical project management, data warehousing & metadata architectures, data integration, relational & dimensional modeling.

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