AI Is Key to Unstructured Data
October 5, 2017
Companies are now inclined to keep every scrap of data they create or collect, but what use is information that remains inaccessible? An article at CIO shares “Three Ways to Make Sense Out of Dark Data.” Contributor Sanjay Srivastava writes:
Most organizations sit on a mountain of ‘dark’ data – information in emails and texts, in contracts and invoices, and in PDFs and Word documents – which is hard to automatically access and use for descriptive, diagnostic, predictive, or prescriptive automations. It is estimated that some 80 percent of enterprise data is dark. There are three ways companies can address this challenge: use artificial intelligence (AI) to unlock unstructured data, deploy modular and interoperable digital technologies, and build traceability into core design principles.
Naturally, the piece elaborates on each of these suggestions. For example, we’re reminded AI uses natural language processing, ontology detection, and other techniques to plumb unstructured data. Interoperability is important because new processes must be integrated into existing systems. Finally, Srivastava notes that AI challenges the notion of workforce governance, and calls for an “integrated command and control center” for traceability. The article concludes:
Digital technologies such as computer vision, computational linguistics, feature engineering, text classification, machine learning, and predictive modeling can help automate this process. Working together, these digital technologies enable pharmaceutical and life sciences companies to move from simply tracking issues to predicting and solving potential problems with less human error. Interoperable digital technologies with a reliable built-in governance model drive higher drug quality, better patient outcomes, and easier regulatory compliance.
Cynthia Murrell, October 5, 2017
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