Characterization

Big data characterization is a technique for transforming raw data into useful information, being used in machine learning algorithms and data mining. Characterization essentially generates condensed representations of whatever information content is hidden within data. Therefore, it can be used as a means of measuring and tracking events, changes and new emergent behaviors in large dynamic data streams.

Some benefits of characterization:

• Can generate useful metrics for tracking and measuring events and anomalies in data sets
• Creates small footprint representations of essential information
• Quickly accomplishes data-to-information conversion, which brings the industry closer to the full data-to-information-to-knowledge transformation
• Is useful for indexing and tagging specific objects, events and other features in a data collection