The Business Intelligence Blog

I liked the recent article of Seth Grimes which talks about Text Analytics Accuracy. His article, today, on Intelligent Enterprise, pointed me to the IBM article on IBM® OmniFind™ Analytics Edition which talks in detail about extracting unstructured data from e-mail, Web pages, news and blog articles and building a data warehouse out of them to unlock the huge potential which was previously untapped.

In recent months/weeks, the focus on unstructured data is becoming more and more as businesses and vendors are starting to understand the power of this unstructured data and how it can text mined and used to the benefit of the exterprises. And its a good this.

A must read. Highly Recommended.

Text analytics enables you to extract more business value from unstructured data such as emails, customer relationship management (CRM) records, office documents, or any text-based data. IBM® OmniFind™ Analytics Edition provides rich text analysis capabilities and interactive visualization to enable you to find patterns and trends hidden in large quantities of unstructured information. The text analysis results from OmniFind Analytics Edition are in XML-format and can also be stored, indexed, and queried in a DB2 database. This allows you to incorporate your text analysis results into existing business applications and reporting tools by using regular SQL or SQL/XML queries. This article provides an overview of text analytics with OmniFind Analytics Edition and describes several ways of bringing its analysis results into DB2, in relational or pureXML™ format.
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OmniFind Analytics Edition provides the ability to interactively explore and mine the results of text analysis, as well as structured data that is typically associated with unstructured text. For those of you familiar with business intelligence applications, you can think of it as content-centric business intelligence, in that it aggregates the results of text analysis to detect frequencies, correlations, and trends. Typical use cases include:

Analysis of customer contact information (e-mails, chats, problem tickets, contact center notes) for insight into quality or satisfaction issues
Analysis of blogs and wikis for reputation monitoring
Analysis of internal e-mail for compliance violations or for expertise location