Summary:

DataRPM is one of a handful of companies trying to move business intelligence into its next generation by incorporating natural language processing and a search-like experience. InterWest Partners led its series A round.

DataRPM, a Fairfax, Va.-based startup that has built a business intelligence product based on search engine technology, has raised a $5.1 million Series A round of venture capital. InterWest Partners led the round, which follows up on a $250,000 seed round the company raised in April.

As we explained in a July post about an “askathon” (essentially, a business intelligence hackathon) the company was hosting, DataRPM is based on search technologies and tries to deliver a search-like experience. Data is indexed rather than modeled, and users perform queries in a search bar using natural language.

instant-home

A screenshot of DataRPM.

The latter feature — natural language queries — is fast becoming a point of distinction among the new breed of startups looking to out-simplify the likes of Tableau. We recently covered another effort in this vein (although one selling its product via appliance rather than the cloud, like DataRPM does) called ThoughtSpot. The stealthy Upshot Data, which won the hackathon at Salesforce.com’s Dreamforce event in November, is based on natural language queries, as well.

We’ll be discussing the future of data analysis at our Structure Data conference next week, including plenty of talk about the promise of technologies such as natural language processing even beyond BI.

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