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A big blog for Big Data.

By | January 7th, 2015 | Analytics, Big Data, Data Science, Hadoop

Practical Tips for Making Hadoop a Productive Environment for Data Scientists

In attempting to work on Hadoop-based data, data scientists face two bad options: use Hadoop indirectly by engaging in a slow and error-prone back-and-forth with “data engineers” who translate your needs into Hadoop programs, or use Hadoop directly by using unfamiliar and unproductive command-line tools that are difficult to master.

By | November 13th, 2014 | Big Data, Data Science, Hadoop, HIVE

There Will Never Be One SQL to Rule All

Many discussions of SQL-on-Hadoop implicitly assume a single engine will emerge to handle all analytical workloads. All workloads will be shifted into Hadoop, eliminating the need for data marts. Sounds great, but it’s not going to happen. To understand why, consider this (oversimplified!) table comparing a few SQL solutions by a variety of different quality attributes: