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Big Data at IBM: Using Watson as an Analytic Tool
The number of companies actively applying Big Data analytics to problems in business, science and society is growing rapidly. One company though, IBM, has been unique in the level of sophistication that they’ve been able to apply Big Data techniques in addressing very challenging questions and problems. IBM is now trying to apply the ‘smart analytic’ capabilities of their Watson question-and-answer technology.
In October, IBM launched the Accelerated Discovery Lab at ADLab in San Jose, California. The goal of the company is to apply Watson technology to specific domains to enhance data exploration and data mining. IBM is applying Big Data analytics to the domains of biology, medicine, finance, weather, mathematics, computer science and information technology, and is also now extending into the area of materials science.
Laura Haas, Directory of Technology and Operations at the IBM ADLab, described the goals of ADLab as follows: “The IBM Research Accelerated Discovery Lab (ADLab) is creating a plug-and-play environment for facilitating this discovery process… It will improve the technology used for discovery, while at the same time, allowing users (for example, the business analyst or scientist) to make new discoveries in their fields more easily, at a more rapid pace.”
Jeff Welser, Director of Strategy and Program Development at the IBM ADLab, said that “The Accelerated Discovery Lab shifts the focus away from just looking through big-data question-and-answer style. Instead of looking for answers that are already known—where its just a matter of finding them—we are learning how do search for things that are not yet known… If we think about Big Data today, we mostly use 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. Whether it’s through exploring thousands of public government databases, searching every patent filing in the world, including text and chemical symbols, to develop new drugs or mixing social media and psychology data to determine intrinsic traits, there’s a big innovation opportunity if companies are able to accelerate discovery by merging their own assets with contextual data.”
