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The Excel connector is especially significant because there are millions of business users skilled in Excel that just don’t have the chops to analyze data stored in Hadoop. There are plenty of startups trying make Hadoop accessible to business users — including Datameer, which provides a spreadsheet interface (and is even a Microsoft partner) — but it’s unlikely that any combination of efforts will match the impact of accessing and analyzing Hadoop data right from the familiar Excel (and PowerPivot) application.
Since October, Microsoft has been publicly working with Hadoop startup Hortonworks to make Hadoop work better in Windows environments. In the process it all but killed the Dryad big data framework it spent years developing. This new strategy includes Hadoop distributions for Windows Servers and the Windows Azure cloud computing platform, as well as a connection to SQL Server. Hadoop on Windows Azure, in fact, is already available in Developer Preview mode and should be generally available by the end of this quarter, according to ZDNet Microsoft insider Mary Jo Foley.
The SQL Server distribution, she reported, should hit preview mode by the end of the quarter and be generally available by the end of June.
On Monday, I quoted Hortonworks CEO Rob Bearden claiming Hadoop could be a billion-dollar market in a couple of years, ultimately ending up as the de facto data platform for next-generation applications. Not everyone buys into this rosy prediction, but Microsoft’s commitment to Hadoop makes it seem a lot more plausible. Sure, EMC (s emc), Oracle (s orcl) and IBM (s ibm) already push Hadoop-based products, but when it comes to sheer number of employees sitting at desktops and hacking away at spreadsheets, it’s hard to discount what Microsoft could mean for Hadoop as a whole.
No doubt, Microsoft’s increased involvement will come up at our Structure:Data conference next month in New York, where execs from several Hadoop vendors, including Hortonworks, will take the stage on March 22 to talk about the future of Hadoop.
Image courtesy of Brian Robert Marshall.