I can say personally I have shifted my research topics to include more statistical/predictive modeling as a component (though generally not the primary one) of my research. So for example, suppose someone had a set of statistical models to describe a system and now wants to optimize it. Most statisticians will shove these models into a black box heuristic such as a genetic algorithm. However, mathematical programmers have known for years that there are better ways to optimize by exploiting special structures of the models. Developing these better methods has become the focus of most my research topics these days.

]]>But I like your definition, too. When you cannot open data using regular data processing software, you know it’s big (:

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I disagree with “I like this definition of big data, since it acknowledges that the challenges do not only lie in the size of the data; complex data in multiple formats and data that changes rapidly is also included.” Big data is by definition large quantities of data at once, if data streams in and can then be discarded, that doesn’t count. ]]>