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Advanced 'Big Data' Analytics with R and Hadoop


"Big Data" Analytics as a Competitive Advantage

Compared to traditional analytics, the so-called Big Analytics presents two competitive advantages: It describes the efficient use of a simple algorithm applied to large datasets without compromising performance and the algorithm's sophistication.

Revolution Analytics addresses both and supports: avoiding sampling and/or aggregation; reducing data movement and replication; bringing analysis close to the data; and optimizing computation speed.

It also delivers optimized statistical algorithms for file-based, MapReduce, and In-Database analytics, and is optimizing algorithms for working with Big Data. Open Source R is memory-bound and not made for Big Data Analytics. Big Computations are an allied challenge, since some algorithms require significant processing capacity and may not run using other data-management paradigms. This paper addresses the integration between R and Hadoop supported by Revolution Analytics.