EPAM Uses Machine Learning to Turn Unstructured Data into Insights for Companies
As a follow-up, unstructured data is the fastest growing form of data. In fact, according to a recent report by Gartner, over 80 percent of enterprises' storage footprint consists of unstructured file data – things like social media posts, customer-generated content, and enterprise assets such as white papers, emails, and more. Companies that aren’t taking advantage of it are missing important insights that can impact their bottom line.
Jitin Agarwal, VP of Enterprise Products for EPAM, a leading global provider of digital platform engineering and software development services, says the ability to quickly consolidate and analyze unstructured data is critical to staying competitive – and he’s seeing this being put into action across a number of verticals.
The demand for these insights is why EPAM this week launched InfoNgen, a content aggregation and sentiment analysis engine that crawls over 200,000 web sources to deliver ready-made, customized insights to companies, taking advantage machine learning to distill the aggregated data.
Customers can quickly find, analyze and share critical information to speed decision-making and track competitive moves. In addition, InfoNgen can be used to:
· Identify market opportunities and industry trends
· Search for hidden patterns and trends in data
· Aggregate intelligence about your brand, customers, partners and competitors
· Gain customer feedback and intelligence on what your customers think about your campaigns
· Keep track of new regulations and discover violations
· Find, monitor and take action on counterfeit and fraud
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