Latest Update made on May 13, 2016.
Hadoop has now been around for quite some time. But this question has always been present as to whether it is beneficial to learn Hadoop, the career prospects in this field and what are the pre-requisites to learn Hadoop? To address each of these questions in detail, our counsellors work tirelessly to keep themselves updated with the industry news and provide the best advice to people regarding - who can learn Hadoop and the career prospects in Hadoop.
By 2018, the Big Data market will be about $46.34 billion dollars worth. This is as per an IDC forecast. The IDC forecast is pretty optimistic as it also predicts a growth of CAGR 58.2% between 2013 - 2020. The Government and Federal agencies of several countries are now beginning to adopt Hadoop because of its open source nature and distributed computing capabilities. The availability of skilled big data Hadoop talent will directly impact the market. Big Data and Hadoop are moving out of its experimental stage and Hadoop is continuously maturing after having completed 10 years. Learning Hadoop will ensure that your base in the field of Big Data is successfully created and will allow you to move to other big data technologies as per the requirements of your industry.
The US will soon be flooded with 1.9 million direct IT jobs and there will not be enough certified professionals to fulfil even a third of them. There have been several headlines about various big data jobs recently-
Professionals who have graduated from college few years ago and who are not into any of the big data positions are enthusiastic to know about the skills and knowledge required to apply for most of the open big data positions. With novel and lucrative career opportunities in Big Data and Hadoop, this is the right time for professionals to learn hadoop, one of the most complex and challenging open source framework.
So many people have told you that Hadoop is the hottest technology right now. So making a career shift towards Hadoop might seem like the best thing to do. But you need to be sure that learning Hadoop will be a good career move for you. Let us see what Industry Experts have to say on this:
Gus Segura, Principal Data Science Engineer, Blueskymetrics - says Yes. Learning Hadoop will ensure that you can build a secure career in Big Data. Big Data is not going to go away. There will always be a place for RDBMS, ETL, EDW and BI for structured data. But at the pace and nature at which big data is growing, technologies like Hadoop will be very necessary to tackle this data.
Students or professionals who have heard about the term “Big Data” are keen to be a part of the digital data revolution that is happening and often ask this question to our career counsellors- “What are the pre-requisites to learn Hadoop?” or “How do they start their career in Big Data?”
This article leads through the hadoop learning path by answering all the questions students encounter before they make a career switch into Big Data Hadoop-
Learn Hadoop to become a Microsoft Certified Big Data Engineer.
Hadoop is becoming the most dominant data analytics platform today with increasing number of big data companies tapping into the technology for storing and analysing zettabytes of data. Anybody with basic programming knowledge can learn Hadoop. A Ph.D. or a Master’s degree is not mandatory to learn Hadoop technology.
Big data revolution is creating tremendous job opportunities for freshers as numerous organizations are looking to hire young talent - but the major roadblock is that freshers lack hands-on working experience with Hadoop. Thus, college graduates from any kind of programming background can learn hadoop by undergoing a comprehensive hadoop training program and working on practical hands-on projects that gives them real time feel of the hadoop environment and experience - that makes them the ideal fit for what employers are looking for!
Demand for Big Data Analytics talent will by far surpass the supply of talent by 2018. According to a McKinsey Global Institute study, it is estimated that in the United States alone, there will be a shortage of Big Data and Hadoop talent by 1.9k people. The demand for quality Hadoop developers will exceed supply by 60%.
Unlike other technologies that can be mastered by oneself, Hadoop is harder and professional hadoop training can help graduates or post-graduates from various backgrounds i.e. Computer Science, Information Technology, Electronic Engineering, Applied Mathematics, etc., get started on their Hadoop career. There are no pre-defined or strict pre-requisites to learn hadoop - if you have the willingness and zeal to pursue a career in big data ,no matter from which background you are- a comprehensive hadoop training can help you get a big data hadoop job.
For the complete list of big data companies and their salaries- CLICK HERE
To learn the core concepts of big data and hadoop ecosystem, the two important skills that professional must know are –Java and Linux. Enterprise folks who have not previously worked with either of these can still get ahead in the hadoop mainstream by just getting their hands dirty on some basic knowledge of Java and Linux.
Hadoop needs to be setup in a Linux based operating system preferable Ubuntu .The preferred method of installing and managing hadoop clusters is through the command line parameters of Linux shell. So for professionals exploring opportunities in Hadoop, some basic knowledge on Linux is required to setup Hadoop. We have listed some basic commands that can be used to manage files on HDFS clusters. These commands can be used for testing purposes and can be invoked through the virtual machines (VM’s) from Hortonworks, Cloudera, etc. or also through your own pseudo distributed hadoop cluster-
Hadoop fs –put
This command is used to upload a file from the local file system to HDFS. Multiple files can be uploaded using this command by separating the filenames with a space.
Hadoop fs –get
This command is used to download a file from the local file system to HDFS. Multiple files can be downloaded using this command by separating the filenames with a space.
Hadoop fs –cat
Hadoop fs –mv
Hadoop fs –rm
Note- To remove a directory, the directory should be empty before using the rm command.
Hadoop fs –copyFromLocal
Hadoop fs –du
Hadoop fs –ls
Hadoop fs –mkdir
Hadoop fs –head
Advanced Java expertise comes as an added advantage for professionals yearning to learn Hadoop but is not among the pre-requisites to learn hadoop. Folks who are honourably interested to pursue a lucrative career in big data and hadoop can get started in hadoop while simultaneously spending few hours on learning basic concepts of java. Hadoop allows developers to write map and reduce functions in their preferred language of choice like Python, Perl, C, Ruby, etc. through the streaming API which supports reading from standard input and writing to standard output. Apart from this, Hadoop has high level abstractions tools like Pig and Hive which do not require familiarity with Java. For detailed understanding on “How much java is required for Hadoop?” – Read More
There is a myth that only professionals with experience in java programming background can learn hadoop. However, the reality is that professionals from Business Intelligence (BI) background, Data warehouse (DW) background, SAP background, ETL background, Mainframe background or any other technology domain can start learning hadoop as most of the organizations across various industries are now moving to Hadoop technology for storing and analysing petabytes of data.
Professionals who enrol for online Hadoop training course must have the following minimal hardware requirements to learn hadoop without having to go through any hassle throughout the training-
Hadoop is a game changer for all big data companies for - making better decisions with accurate big data analysis. Learning Hadoop is foremost step to build a career in big data.
Hope this blog post will help you and other readers along your journey to learn hadoop. Wish you and other readers the best as you transform your career by learning Hadoop or any other big data technologies! If you have any questions, feel free to ask in the comments below.