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Hadoop is widely perceived as the future of big data, and for the most part this has proven true. The market for Hadoop expects a compound annual growth rate of more than 60 percent through 2016, according to IDC data.

This increased adoption allows existing technologies and innovative projects to leverage the strengths of Hadoop and rapidly join the big data community.

In 2016, we can expect to see more advancements in Hadoop, leading to an even bigger role in near real-time data management, cleansing, and security. There will be newer tools, more mature processes and standardized technologies within Hadoop.  

So what specifically is on the horizon for Hadoop in 2016? Next-level capabilities, that’s what. Here are just a few.

Advanced Analytics

Hadoop MapReduce isn’t just a data platform which can manage large data sets, but a computational platform that enables advanced forms of analytics, such as data mining, statistical analysis, text analytics, graphs, and ad hoc algorithmic approaches. However, Hadoop’s analytic power has the ability to determine the root cause of various issues like customer churn, modernize actuarial calculations, and more.This flexibility is why Hadoop appeals to leading enterprises.

Rapid ANSI Compliant

According to Forrester, rapid American National Standards Insinuate (ANSI)-compliant SQL-on-Hadoop options will lead to the creation of “immediate opportunities for Hadoop to become a useful data platform for enterprises”. This is due primarily to their accessibility from existing systems and data-management professional familiarity.

Diverse Data Support

Hadoop supports widely diverse data and file types which help enterprises extract business value from new or previously unmanageable data. This improves overall decision-making and operational efficiency.

With data growth expanding every day, we can assume that 2016 will be the year of big data expansion. Hadoop, with its myriad of enterprise-relevant capabilities is leading the way.

If you’d like more in-depth information about Apache Hadoop implementation or training programs, visit or contact us at [email protected] You can even follow us on Twitter @OSSCube.

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