Small data is data in a volume and format that makes it accessible, informative and actionable.

Small data typically provides information that answers a specific question or addresses a specific problem. Examples of small data include baseball scores, inventory reports, driving records, sales data, biometric measurements, search histories, weather forecasts and usage alerts.

The term small data contrasts with big data, which usually refers to a combination of structured and unstructured data that may be measured in petabytes or exabytes. Big data is often said to be characterized by 3Vs: the volume of data, the variety of types of data and the velocity at  which it is (or must be) processed, all of which combine to make big data very difficult to manage. Small data, in contrast, consists of usable chunks.

The Small Data Group offers the following explanation:

Small data connects people with timely, meaningful insights (derived from big data and/or “local” sources), organized and packaged – often visually – to be accessible, understandable, and actionable for everyday tasks.

 

This was last updated in June 2014
Contributor(s): Ivy Wigmore
Posted by: Margaret Rouse

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