Sypherlink, a technology firm that accelerates the data-sharing process across multiple data sources and provides information access controls, has launched unique solutions for data cleansing and standardization.

Harvester: Arbiter is a data analysis, data integrity and consistency tool that can be used to normalize related information across a set of data sources, simplifying the data profiling and cleansing problem. Learning Lexicon applies sophisticated filtering technology to standardizes particular sets of information around a common terminology and employs learning algorithms to continuously improve the recognition of like entries.

The foundation of Sypherlink: Harvester is its patent-pending heuristics matching technology, which provides critical metadata discovery, analysis and mapping functionality in an unattended fashion. Arbiter and Learning Lexicon leverage this foundation to deliver data quality and integrity.

Arbiter can be used to verify the integrity of the information within a single data source. Unlike other tools for data cleansing/data quality, Arbiter utilizes advanced heuristics to automatically determine which fields are related, and which should be in the same format. Plus, it does this simultaneously across multiple data sources, and without manual intervention.

Learning Lexicon enables users to apply a standard lexicon and Sypherlink's heuristic analysis tool to assign a particular identification based on the mapping of an item to a lexicon identifier. When particular sets of information are standardized around a common lexicon, then statistical reports can be built and conclusions about business practices can be drawn.

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