Unlocking the value from your Dark Data through AI & ML

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  • Published date: February 14, 2020 07:47
  • Modified date: February 14, 2020
    • Sunnyvale Operational Headquarters 1285 Oakmead Parkway, Sunnyvale, CA, 94085, USA. Sun Valley, California, United States

Gartner defines dark data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing). Similar to dark matter in physics, dark data often comprises most organizations' universe of information assets.

These assets include emails, contractual documents, multimedia, and other intellectual property. Parsing, tagging, linking and searching all this dark data is the greatest immediate opportunity for most businesses to unlock the value.

With the advances in NLP and Machine learning, making sense out of this data and generating actionable insights to surface the risk, liabilities, and opportunities to renegotiate contractual terms is a low hanging fruit to prove the ROI of the AI initiatives in a company.

It's a good idea to enrich organizations data with external data sources that will help in creating new services. The data from Experian, Nielsen and other data aggregators are being used by companies that provide identity theft management, social lending platforms, and others to make instant decisions by applying various machine learning models.

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