At the recent Intel Analytics Summit, our first panel discussion featured a conversation on distributed analytics.

This panel offered a lively look at topics that are close to the heart of anyone focused on extracting value from big data. While the topics were wide-ranging — from foundational technologies to applications like machine learning, the centerpiece of the discussion was a deep dive into the advantages of distributed analytics.So what is distributed analytics? At the most basic level, distributed analytics spreads data analysis workloads over multiple nodes in a cluster of servers, rather than asking a single node to tackle a big problem.

The same algorithms run across each of the nodes, processing a subset of the data. When the processing concludes, the data sets are aggregated, or brought back together, to generate collective insights.To read this article in full or to leave a comment, please click here

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