What is Meta-data?
Meta-data 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. Metadata has been around since the first program was written. The word metadata was first recorded in the dictionary around 1980’s but its usage goes back all the way to 1960’s.
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 provides us with a reference to useful data, and provides us with definitions that allow us to understand that data: its definition, its usages, its ownership, and its 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?
Poor documentation often leads to loss of 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’s data and how to use it
To help allow your organization share data in a consistent way without duplication
To preserve the value of the data saving it from being useless due to changes to the data over time
To help new employees understand the organizations data with a smaller than normal learning curve
Some sources for Metadata in an organization:
Conceptual, Logical and Physical Data Models
Attribute Characteristics – field type, field size, etc.
Data Source System(s)
Data Quality Rules Copyright © Unissant, Inc. All Rights Reserved. Page 4 of 5
Data Quality Issues and more
In conclusion, 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 I will try to dive deep into the types and sources of
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 Meta-data. His expertise includes enterprise information management, technical project management, data warehousing & meta-data architectures, data integration, relational & dimensional modeling.