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Hadoop is a software framework that offers support to data-intensive distributed applications. It is open-source software that enables applications to work with multiple nodes and petabytes of data. It is the most popular Big Data technology that was developed in the lines of Google’s MapReduce and Google File System (GFS) papers. It provides the resources required for using an enormous cluster of computers to store large amount of data which can be operated on the parallel.

A brief overview

As free license software from Apache, Hadoop has emerged as a popular means for managing big data, including complex, structured and unstructured data. Its popularity stems from its ability to store, analyze and access large amounts of data in a cost effective manner across clusters of community hardware.

Significance of Big data Solution

As per researches, every day we create an average of 2.5 quintillion bytes of data, which is going up at an incremental pace. Millions of people across the world log on to Facebook to change their profile picture and more data are generated from emails and search engines that get simply dumped in a cluster of data.  Among all this inconsequential data there is a large percentage of data that can prove to be a gold mine for business intelligence, which can make or break market trends. 80% of the data captured is unstructured and gathered from diverse sources including social media posts, digital media including images and videos, GPS signals, transaction records, to name a few. All this constitutes Big Data and companies seek cost-effective and innovative information processing systems to gain insights by comprehensively analyzing the data.

Where does Hadoop come in?

Hadoop provides a cost-effective solution for managing big data. Its fluid system enables the business to access the data in a time-efficient manner, across geographies and devices, that too in a secure environment. As more data is generated each day, data irrelevance is also occurring at the same pace; hence, the timing is highly essential. Further, a cost effective solution will enable businesses to earn higher ROI and with mobility devices being used for most business transactions, data access on mobile devices becomes highly essential.

Best features of Hadoop

  • Scalable -  it’s open source nature makes Hadoop accessible for businesses on the early stage of the growth curve, hence, the system will grow with the business
  • Cost efficiency – a sizeable decrease in cost per terabyte of storage can be experienced with big data with its cluster of computers for storage.
  • Handling errors – if a node is lost, the system redirects the work to another location, so data processing continues without any delay
  • Flexibility – data from multiple sources and formats can be stored and processed on Hadoop, a pre-defined schematic is not essential for data analysis.

Hadoop Applications

Hadoop allows the user to frame questions to reveal answers to standard problems, thereby making all data usable. It makes complete data sets instead of mere data samples available for analysis. This enables businesses to do in-depth analysis and come up with immediate results for –

  • Ideas on new products
  • Research, development and marketing analysis
  • Overview of daily operations
  • Productivity measurement
  • Network monitoring
  • Log and/or click analysis

Big Benefits of Learning Hadoop

benefits of learning hadoop

Big career opportunity

A survey among 90 executives from Fortune 100 Senior Business & Technology executives showed that at least 90% organizations were already working with Big Data. There is an urgent need for IT professionals with Hadoop experience to meet the needs of the growing industry demands. It has been proven that data harnessing can play a major role in competitive plans and strategy development which requires critical skills. Hence, businesses are willing to pay high prices for professionals with the right skills.

Career in hadoop

Big Salary packages

As data is the backbone of any business, there is and will always be a thriving need for fast data processing and timely access. Hadoop with its advanced system addresses this need and hence, in any company the Hadoop specialist will always be well-paid. In fact, IT professionals with skills in Big Data- related languages and databases are enjoying some of the healthiest pay checks. As hiring postings for Hadoop has gone up by 64% in the past year, Hadoop has emerged as the leader in Big Data category. Hadoop pros are paid an average salary of over USD 109,000, which is higher than the average of USD 106,000 for other big data jobs including Unix, SAP, IBM Mainframe, VB, .NET, MySQL, C++, Java Script, VM Ware and Teradata.

Big company hiring

There are more than 17,000 employees with Hadoop skills across major companies such as Microsoft, yahoo, Google, Cisco, eBay, IBM, LinkedIn, Oracle, Amazon, Tata and HP. Companies are seeking :

    • Big data visualize
    • Data scientist
    • Big Data analyst
    • Big data engineer
    • Big data architect

    Big data and Hadoop market growth

    Hadoop market  growth

    A positive trend can be observed in demand for Hadoop specialists. Hadoop is touted to be the future of big raw data, with its ability to process raw data into actionable analytics with little additional tools or professional consulting. It lays the foundation for better business intelligence, and at a very price. With more vendors developing turnkey solutions to support Hadoop, tools are available for shortening the learning curve and enjoying ROI faster on a Hadoop investment. Their easy integration with Hadoop, makes the third-party solutions of existing BI set-up also synchronize with the Hadoop system easily.

    As an open source platform with an active developers’ community who contribute greatly towards its betterment, Hadoop architecture is undergoing massive evolution. There are many Hadoop tools that are still in their prototype stage or undergoing applications testing. Gradually, we can observe Hadoop emerge into a turnkey system that captures, organizes and analyzes data.