The workshop will illustrate a number of techniques for data modelling that help us extend our small data capabilities to the world of big data: sampling, resampling, parallelization where possible, ...

The workshop will illustrate a number of techniques for data modelling that help us extend our small data capabilities to the world of big data: sampling, resampling, parallelization where possible, etc. We will leverage the functional architecture of R and its statistical analysis prowess in small data environments using the mapreduce technique embedded in Hadoop to tackle large data analysis problems. Particular attention will be paid to the ubiquitous --but non-scalable-- logistic regression technique and its big data alternatives.

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