7 Ways Mining Unstructured Text Data with DataScava is Different

It’s always true been true in computing that garbage in is garbage out.

This certainly is the case when it comes to working with unstructured text data, which by 2022 will make up more than 90 percent of the world’s electronic information, delivered in business reports, research papers, emails, and other formats – all written in different styles and using terms whose meaning differ from sector to sector.

It’s become an axiom that data scientists spend 80 percent of their time dealing with data preparation problems — leaving only 20 percent for algorithm development, model training and tuning, and machine learning.

Use Your Business Language and Subject Matter Expertise
Today, the technology exists to use your business language and subject matter expertise to quickly and accurately mine raw text so you can unlock its value.

It’s a self-service system that curates, searches, filters and routes raw unstructured text data to make it more accessible, understandable and actionable.

A tool that uses your company’s domain-specific topics, searches and filters tuned to your business and always in your control.

And works as an alternative or adjunct to NLP/NLU.

It’s called DataScava.

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