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It’s not everyday that you hear of a company manages to quietly raise two venture rounds from A-list investors while spending two years developing its technology in stealth mode. But that is exactly the story behind big data analytics and business insights (BI) startup EdgeSpring, which today publicly launched its product and announced $11 million in Seed and Series A funding from Kleiner Perkins Caufield & Byers (KPCB) and Lightspeed Venture Partners.

Founded by former Salesforce, IBM and Oracle execs, EdgeSpring is among a new class of BI solution that eliminates the need for expensive and bottleneck-inducing IT and data-scientists to manage requests from everyday business users. Rather, the company offers the lamen a next-gen search-based solution that relies on artificial intelligence, compression technology, and schema–free visualizations to anticipate the questions a user may ask and then deliver actionable responses in near real-time. The aim is to make it possible for the marketing or finance exec to draw insights from data of any size or structure.

“From day one, our vision was to democratize information access in the enterprise,” EdgeSpring founder and CEO Vijay Chakravarthy says.

EdgeSpring is available as a cloud-based or on-premise solution. The platform offers integrations with SQL, Hive, salesforce.com, and other data sources, making it relatively straightforward to import large volumes of data from across a business.

It seems that every company has collected massive amounts of data about its business, a situation that’s only accelerating with the rapidly declining cost of data storage and the parallel increase in new data being created. The issue becomes how to make value of these mountains of information. When the data set grows beyond the size that can be reasonably be managed through spreadsheets, charts, and manual queries – something that is no longer realistic for all but the smallest and most unsophisticated businesses – companies turn to BI tools that can bridge the speed and scale gap.

As Lightspeed managing director Ravi Mhatre wrote recently:

I believe that to harness the power of this data revolution and gain a competitive edge, companies need to be able to do more than create and query their big data stores. They need to focus on making this big data fast, intuitive and easy to manipulate in new and interesting ways.

While the term “big data” is arguably overhyped, the innovation that many companies in this category are driving is real. A 2012 IDC research report on the business analytics software industry indicated that the market grew 14.1 percent in 2011 and should reach $50.7 billion in gross sales by 2016. EdgeSpring is part of this revolution, but is certainly not alone. Other exciting companies include Qliktech, Tableau, and Chiliad among dozens of others.

Since introducing its product into private beta several months ago, the company has added numerous enterprise customers including AppSense, Demandbase, Docusign, Equinix, Lithium, Netflix, Pandora, SpruceMedia, and Xactly, among others.

In addition to its commercial product, EdgeSpring has also been developing a Crunchbase visualization, CrunchEdge, as a public demo of its platform’s capabilities. CrunchEdge will be available at the beginning of June, allowing users to analyze and manipulate the startup and venture capital data according to various visualizations, filters, and associations. Having demoed the product, I can confidently say that it will add a level of clarity and insight never before available, and could dramatically impact the way that investors, entrepreneurs, and even journalists look at the startup ecosystem.

With the constant introduction of new and more powerful analytics tools, the value of business data is growing by the day. EdgeSpring has come out of its stealth period with an novel product and an equally impressive list of investors and early customers. In a competitive market, the company now faces the challenge of both selling enterprise customers on its value and keeping up with the fierce competition within the category.