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October 11, 2013

IBM opens Accelerated Discovery Lab for big data insight

The new lab provides access to various data sources and research capabilities

By CBR Staff Writer

IBM has opened the new Accelerated Discovery Lab in San Jose, US to help clients to find out insight from disparate data sets.

The new lab provides access to various data sources, research capabilities for analytics including domain models, text analytics and natural language processing derived from IBM Watson as well as domain expertise.

According to the company, the integration of resources reduces time to analyse the results like cost savings, revenue generation and scientific impact that affect businesses.

IBM Research Accelerated Discovery Lab strategy and program development director Jeff Welser said that Big Data is mostly used it to find answers and correlations to ideas that are already known.

"Increasingly what we need to do is figure out ways to find things that aren’t known within that data," Welser said.

The companies may miss insights that can be found by combining their understanding together with other experts, data sources, and tools to provide different perspective and discover new value in their Big Data, the company said.

Accelerated Discovery Lab uses research and product technologies for analytics on a scalable platform to authorise subject matter experts to detect and work with assets including datasets, analytics, and other tools of interest relevant to their project.

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The new lab enables collaboration across projects and domains to support discovery by applying non-proprietary assets to subsequent projects

IBM Research Accelerated Discovery Lab Technology and Operations fellow and director Laura Haas said that the history of computing shows that systems commoditise over time.

"Our environment will provide critical elements of discovery that allow domain experts to focus on what they do best, and will couple them with an intelligent software partner that learns continuously, increasing in value over time," Haas added.

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