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Summary:

Natural-language processing powers the Instant Answers feature from business intelligence startup DataRPM, which could help more people easily get insights from their big sets of data.

More companies are realizing that analyzing their big data can lead to insights that increase revenue and produce other business breakthroughs. But getting good answers isn’t always easy, often requiring IT administrators to take charge and leaving all but a handful of business executives equipped to use software. One startup has a nice and simple idea for big data analytics: Google-like search.

Fairfax, Va.-based DataRPM on Tuesday announced that it has raised $250,000 from angel investors and rolled out a new feature for its business-intelligence Software as a Service (SaaS) called Instant Answers. The feature uses natural-language processing to figure out what users want to see, based on typed or spoken queries, and displays the visualization that the software thinks is the best fit. Users can filter and comment on the results.

While methods and purposes vary, the idea of making software or a site respond to limited user input isn’t new. The approach reminds me of Facebook’s Graph Search, which rapidly delivers several options for search results based on likes, friends and other user information. Software from BeyondCore also comes to mind, as it quickly displays graphs and audibly speaks out its findings to show the biggest drivers of, say, revenue. BeyondCore CEO Arijit Sengupta took a few minutes of stage time at GigaOM’s Structure:Data conference in New York last month to show off the software.

More natural-language processing and machine-learning technology could make DataRPM’s Instant Answers tool a better choice in a crowded market. Perhaps the SaaS could keep tabs on which data users call up and how users might modify their searches if they don’t get the data or visualizations they want the first time around. Later, it could predict what users want. The original Instant Answers is nevertheless a good start.

Feature image courtesy of Shutterstock user anaken2012.

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