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Need to plumb Hadoop data lakes? This new tool can help

Need to plumb Hadoop data lakes? This new tool can help

Think Big's Dashboard Engine aims to put big-data insights within closer reach for business users

Think Big on Monday took the wraps off its Dashboard Engine for Hadoop, which aims to make it easier for business users to extract insights from the vast lakes of data stored in Hadoop.

The development comes hard on the heels of last week's launch of AtScale's Intelligence Platform, which has a similar intent.

Virtually endless streams of data from Web browsers, set-top boxes and contact centers land in Hadoop within many enterprises, but they often aren't accessible to a company's business users through "downstream" analytics tools, said Ron Bodkin, president of Teradata-owned Think Big.

Whereas AtScale's answer to that problem focuses on forging a connection via Microsoft Excel and other commonly used business-intelligence tools, Think Big hopes instead to remedy the situation with the Dashboard Engine for Hadoop, which offers a way for organizations to get summarized Hadoop data in less than a second without having to go through transformation and modeling processes.

The tool distils terabytes of data per hour into billions of aggregates available for querying. It also accommodates multistructured data of many kinds, including click-stream, mobile-phone logs, sensor and JavaScript Object Notation.

Among the results: Hospital groups can use the Dashboard Engine for Hadoop to track provider utilization, understand prescription trends and monitor disease outbreaks, Think Big said. Manufacturers can use it to monitor sensor data, while retailers could put it to work assessing both consumer responses to ads and on-site behavior so they can react with price adjustments or special offers, for example.

Now in beta, the Dashboard Engine for Hadoop will be generally available in the third quarter. Pricing details were not disclosed.


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Tags open sourcebusiness intelligencesoftwareapplicationsTeradatadata mining

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