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Summary:

ClearStory Data has raised $9 million from from KPCB, Andreessen Horowitz and Google Ventures in an attempt to plant its stake in the world next-generation analytics platforms. Big data is presenting a big challenge for business users, and they need help making sense of it.

ClearStory Data, the much-hyped Palo Alto, Calif., startup trying to make easy work of complex analytics, plans to announce Wednesday that it has raised a $9 million Series A round from Kleiner Perkins Caufield & Byers, Andreessen Horowitz and Google Ventures as the company inches closer to general availability in 2013. ClearStory is one of a handful of startups trying to blunt the expected shortage in skilled data analysts by making it as simple as possible to work with large, disparate datasets. It’s also one of the most innovative.

Although the company’s still trying to keep mum about the details, I had a demo recently and can vouch for the cloud-based service in its current state. More impressive than the actual visualizations and analytical process is the variety of data sources the platform can handle. Users can integrate data from nearly any public or private source, and ClearStory will also surface relevant datasets from third-party sources. It’s like a data marketplace baked right into a business intelligence system.

Sharmila Shahani-Mulligan

Sharmila Shahani-Mulligan

Co-founder and CEO Sharmila Shahani-Mulligan explained to me how it might work in the case of a video game launch. A company might track activity on its Facebook launch page as it’s happening, as well as on Twitter and from Omniture or Google Analytics. Once players actually start playing, the company could work in data about who’s playing it and where from the Xbox Live service. Over the next couple days or weeks, it might start analyzing its own sales data, marketing spend, reviews from gaming web sites and perhaps data from a service such as Nielsen on consumer awareness.

Shahani-Mulligan said the company’s early users are stoked about being able to analyze and access all the data sources they want from a single platform. “Every customer we’re in front of … every single one of them has a huge appetite for that,” she said.

That’s not to say the analytics experience is subpar, though. Once users choose their data, ClearStory automatically “harmonizes” it for them — which is a fancy way of saying it finds the common metrics (e.g., time and place) so the datasets can be combined without manual labor. At that point, it’s similar in feel to Platfora’s Hadoop-based BI software or a friendlier version of Tableau — pretty visualizations and lots of dragging, dropping and collaboration.

However, just because it might have struck an impressive first blow with its methods for data support and discovery, ClearStory is going to fight the same uphill battle as its well-funded (or, at least well-conceived) peers such as Platfora, Datahero and Chartio. Business users might love them, but legacy BI vendors have large sales teams and track records. And the “next-generation” space is currently filled by the likes of Tableau, QlikView, Jaspersoft and Pentaho, as well as a suite of specialized services for areas such as marketing, media and log file analysis.

But then again, that’s what makes the cloud computing era so great. Business users need better analytics tools, and now they have a plethora of options that should help them become more productive at a price point that even their corporate credit cards can handle. It’s a bottom-up world: Services that really work will become indispensable with their users and ultimately find themselves as a line item on corporate budgets for years to come.

Feature image courtesy of Shutterstock user sellingpix.

  1. Ladies and Gentleman start your engines….

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  2. Software like this will undoubtably be useful if it works. Color me skeptical though that it can automatically “harmonize” data though. Unless it’s specifically designed for a very specific use case (like analyzing website traffic, or log files), I don’t see how it can determine the appropriate metrics for any general data.

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