Big Data: A Beginner's Guide To Using Data Science For Business (Transforming Information, Deep Learning, Boost Profits, Business Intelligence) by Eliot P. Reznor

Author:Eliot P. Reznor
Language: eng
Format: azw3
Publisher: EPR Publishing
Published: 2017-08-21T07:00:00+00:00

The importance of open-source tools is also signified by the fact that more and more distributors and vendors who conventionally depended on proprietary platforms are now using this technology. For instance, in 2012, VMware released a new open-source project known as Serengeti, which is built to allow Hadoop run alongside the vSphere cloud built by the company.

Open-source tools also have their flaws. Primarily, open-source tools that are for free usually does not offer customer support; you might need to buy or subscribe to the premium version to receive this service. While an open-source tool could be beneficial in experimenting with new tools, it normally does not need trained It professionals who understand the open-source tool.

The biggest risk is that the developers of open-source tools may choose to discontinue developing the tools or may move to other companies. This may lead to outdated software that may not be suited for future challenges in Big Data.

Hence, the decision to employ an open-source tool should be made cautiously. Business organizations must consider not only the affordability of open source tools, but also have a comprehensive understanding of the advantages and disadvantages of the various open-source tools as compared with enterprise technology for Big Data.

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