Birst Lowers Hadoop Adoption Barrier

Treats Big Data As If It Were Ordinary Data

So you've wrestled that Hadoop elephant into a cluster. Now what? How do you get the beast's huge flat files to make sense? The precious hard-won data in Hadoop isn't exactly suited to business intelligence and making it actionable is a lot of work.

Enter Birst, the analytics house, which says it's taken some of the pain out of accessing Hadoop data for mid-sized companies that may not have many priests on staff steeped in Hadoop's secrets by front-ending the thing with its own multi-dimensional database and analytics, saving the user from having to supply the nasty ETL code needed to pry the data out of Hadoop and knock it into workable shape.

Basically Birst has lowered the Hadoop adoption barrier by letting users treat Big Data like an ordinary data set and ask it a broad set of questions. A company now only needs a half-a-developer to do the work, it says, not a handful.

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See also Birst press release Birst Makes Big Data Accessible to Midsize Organizations

With Birst's agile BI solution and Hadoop's massive store, business users can now:
- Obtain high level analytic insight on massive amounts of data. Birst creates multi-dimensional models from subsets of Hadoop data and allows business users to browse, query or visualize big data
- Seamlessly elect between real-time access to Hadoop data or integrating Hadoop data with other data sources including SAP, SalesForce, operational and financial information into automatically created multi-dimensional datasets.