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Waiting for Big Data...

Aurélie Barbaux

Publié le

Waiting for Big Data...

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Big data has received massive publicity and is mentioned at every conference and in every manufacturing or research project. In France, it is the only technology to be both one of French Minister for Industrial Renewal, Arnaud Montebourg’s 34 Nouvelle France Industrielle (New Face of Industry in France) projects, and one of seven goals of the Innovation 2030 Commission, chaired by French businesswoman Anne Lauvergeon aimed at bringing to light national champions. And rightly so. According to researchers at the CNRS (French National Center for Scientific Research), big data has many industrial applications. It is defined using predictive mathematical models created from real data, which are more reliable than simulation. Are they really more reliable? That remains to be seen. For the time being, big data is used primarily by marketing experts trying to make sense of a data deluge not previously collected: the wealth of digital data generated by Internet users. In the future, billions of connected devices will be generating digital data. Hence the idea of predicting behavior patterns in digital data. This means using simulation, right? Not exactly. Big data extracts behavior patterns by taking sensor data rather than physics into account. Preconceived models are replaced by direct observation. “We’re reinventing physics” say enthusiastic researchers. Well, almost. The experts nevertheless admit that, “Although big data enables us to predict what’s going to happen, it doesn’t explain why.” Big data holds great promise for identifying optimum operating conditions in complex systems (airplanes in flight, industrial processes, vehicle traffic, etc.), but it is not expected to replace simulation. At any rate, not at our ten champions who have made this technology one of their key skills for industrial success. And not at some of the world’s most successful research laboratories either, who are tackling ever more ambitious, giant-size research projects requiring more and more computing resources. At least, not right away.

Aurélie Barbaux

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