November 20, 2015
(This blog post is an extended version of an October 12, 2015 Le Monde op-ed article (in French)) Our society is increasingly relying on algorithms in all aspects of its operation. We trust algorithms not only to help carry out routine tasks, such as accounting and automatic manufacturing, but also to make decisions on our […]
Read moreFebruary 8, 2015
Big Data, and its 4 Vs – volume, velocity, variety, and veracity – have been at the forefront of societal, scientific and engineering discourse. Arguably the most important 5th V, value, is not talked about as much. How can we make sure that our data is not just big, but also valuable? WebDB workshop, which […]
Read moreNovember 8, 2014
Most professional fields, whether in business or academia, rely on data and have done so for centuries. In the digital age and with the emergence of Big Data, this dependency is growing dramatically – perhaps out of proportion to its current value given the concepts, tools, and techniques presently available. For example, how do you […]
Read moreOctober 30, 2013
“Both theoretical and empirical research may be unnecessarily complicated by failure to recognize the effects of heterogeneity” – Vaupel & Yashin Big Data is daily topic of conversation among data analysts, with much said and written about its promises and pitfalls. The issue of heterogeneity, however, has received scant attention. This is unfortunate, since failing […]
Read moreMarch 6, 2013
Big Data should be Interesting Data! There are various definitions of Big Data; most center around a number of V’s like volume, velocity, variety, veracity – in short: interesting data (interesting in at least one aspect). However, when you look into research papers on Big Data, in SIGMOD, VLDB, or ICDE, the data that you […]
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