In the IT world, clearly big data has attracted a lot of attention from various sectors and the last two years have seen a significant investment in various big data projects and many more startups. According to a new market report published by Transparency Market Research, the global big data market was worth USD 6.3 billion in 2012 and is expected to reach USD 48.3 billion by 2018. In 2014, one will see companies reporting the benefits of their big data projects and further implementing analytics applications on top of big data infrastructure. Bottom line is big data hype may subside but real time project implications and value for the investments would surface in this year. Given that the implementation of projects by various firms is going to continue, the demand for big data talent will continue to rise and this career path is sure to be a challenging and rewarding one.
Amongst the existing big data technologies, Apache Hadoop and its various components are the most popular management solutions for handling big data. Since these technologies are specifically designed to handle massive amounts of data using distributed computing framework, there is a huge demand for the right kind of big data talent. Typically a big data analyst should have good knowledge on MapReduce programming to query and analyze data sitting in the big databases such as Hadoop. Java is the most popular language for executing MapReduce programs on Hadoop and other alternatives which exist are Hive, Pig etc. One can also use other languages such as R, Python, Ruby, Perl, C++ and more to execute MapReduce programs on Hadoop. These along with Hive and Pig are considered as non-Java big data languages in order to query the Hadoop database.