SAS Text Miner Promises Unstructured Insight
July 10, 2015
Big data is tools help organizations analyze more than their old, legacy data. While legacy data does help an organization study how their process have changed, the data is old and does not reflect the immediate, real time trends. SAS offers a product that bridges old data with the new as well as unstructured and structured data.
The SAS Text Miner is built from Teragram technology. It features document theme discovery, a function the finds relations between document collections; automatic Boolean rule generation; high performance text mining that quickly evaluates large document collection; term profiling and trending, evaluates term relevance in a collection and how they are used; multiple language support; visual interrogation of results; easily import text; flexible entity options; and a user friendly interface.
The SAS Text Miner is specifically programmed to discover data relationships data, automate activities, and determine keywords and phrases. The software uses predictive models to analysis data and discover new insights:
“Predictive models use situational knowledge to describe future scenarios. Yet important circumstances and events described in comment fields, notes, reports, inquiries, web commentaries, etc., aren’t captured in structured fields that can be analyzed easily. Now you can add insights gleaned from text-based sources to your predictive models for more powerful predictions.”
Text mining software reveals insights between old and new data, making it one of the basic components of big data.
Whitney Grace, July 10, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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