Text Analytics

Big Data are characterized by a variety of content including text data which can be customer product reviews, service center notes on product issues and repairs, and call center recordings on customer complaints to mention just a few. Text data are full of Rich Information which, as for numerical data, must be extracted and made useful.

Text data, unlike numerical data, are unstructured: they do not follow well-defined patterns and rules so that mathematical and statistical methods are difficult, but not impossible, to apply. They are prone to wide variations in spelling, grammar, idioms and jargon, syntax, and abbreviations issues that complicate processing and analysis. In addition, there are many “stop words” that are used (e.g., articles, conjunctions) that have to be filtered since they add little to no insight.

Finally, words have homonyms, heteronyms, polysemes, synonyms, antonyms which complicate deciphering meanings.

Data Analytics Corp. provides analytical capabilities for moving you across the Analytical Bridge with unstructured text data:

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