Hadoop

Big data infrastructure goes far beyond Hadoop

06th Feb `14, 11:26 PM in Hadoop

Wikibon Principal Research Contributor Jeff Kelly provides an inclusive basic tutorial of the big data environment, including technologies,…

BDMS
Guest Contributor
 

Wikibon Principal Research Contributor Jeff Kelly provides an inclusive basic tutorial of the big data environment, including technologies, skill sets, and use cases, in “Big Data: Hadoop, Business Analytics and Beyond”, and while the environment starts with Hadoop and Map Reduce, it extends far beyond that. While parts of this report may seem basic to technical readers, it provides an excellent overview of technologies, pros and cons, and market issues such as the lack of trained technical personnel and data scientists.

To learn more about what is happening and how your organization can start gaining business advantage through new Big Data technologies and processes, watch theCUBE’s big data event, BigDataSV 2014, on SiliconAngle February 11-13.

Hadoop is often considered the central technology for big data, and Kelly provides a good basic discussion of how it works, how it differs from traditional RDBMS technology, and its pros and cons. However, he goes beyond that to discuss NoSQL and massively parallel analytic databases in general terms and concludes that a full big data processing environment requires all three as well as the traditional RDBMS data warehouse to support the full range of data capabilities companies need.

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