What are the Pre-requisites to learn Hadoop?

What are the Pre-requisites to learn Hadoop?

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-

  • Best Salary Boost in 8 years awaits US professionals in 2016, STLToday
  • Geeks Wanted! Big Data Companies Push Data Scientist Development, Forbes
  • Data Scientist-The Sexiest Job of 21st Century, Harvard Business Review
  • In a Data Deluge- Companies Seek to Fill a new role, Technology Review

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?”

Work on Hands on Projects in Big Data and Hadoop

Prerequisites to Learn Hadoop

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-

Who should learn hadoop

1) Who should learn Hadoop?

2) Skills required to learn Hadoop

3) Knowledge required to learn Hadoop

4) Hardware Requirements to Learn Hadoop 

Learn Hadoop to become a Microsoft Certified Big Data Engineer.

Who should learn Hadoop?

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

Skills Required to Learn Hadoop

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.

Skills Required to Learn Hadoop - Linux

Hadoop needs to be setup in a Linux based operating system preferable Ubuntu [1].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-

1) Command for Uploading a file in HDFS

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.

2) Command for Downloading a file in HDFS

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.

3) Command for Viewing the Contents of a file

Hadoop fs –cat

4) Command for Moving Files from Source to Destination

Hadoop fs –mv

5) Command for Removing a Directory or File in HDFS

Hadoop fs –rm

Note- To remove a directory, the directory should be empty before using the rm command.

6) Command for Copying files from local file system to HDFS

Hadoop fs –copyFromLocal 

7) Command to display the length of a file

Hadoop fs –du

8) Command to view the content of a directory

Hadoop fs –ls

9) Command to create a Directory in HDFS

Hadoop fs –mkdir

10) Command to display the first few lines of a file

Hadoop fs –head 

Skills Required to Learn Hadoop– Core Java

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

Click here to know more about our IBM Certified Hadoop Developer course activated with free Java course


Knowledge Required to Learn Hadoop for Experienced Professionals from different backgrounds

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.

  • For professionals from BI background, learning Hadoop is necessary because with data explosion it is becoming difficult for traditional databases to store unstructured data. Hadoop still has a long way to go when it comes to presenting clean and readable data solutions. BI professionals still use EDW and HDFS is unlikely to replace EDW. but there are many situations where Hadoop is much better suited than EDW. Hadoop does extremely well with file based data which is voluminous and diverse. This is where the traditional DBMS falls short. Professionals working in the BI domain can use BI equivalent of Hadoop popularly known as Pentaho.
  • For data warehousing professionals - it is a good time to learn Hadoop. Firms like Deutsche Telekom, EDF, HSBC, ING Vysya Bank all bet huge on Hadoop being the core data framework. But then all experts agree that Hadoop adds more to any data framework than it substracts. Data warehousing professionals are not going to lose their jobs - nor is EDW going to be completely replaced by Hadoop.                                                                                                                                                                                                                                                   Adding Hadoop to their skills is only going to open up more career options for data warehousing professionals. 3-4 years ago, when Hadoop was still relatively new, there was a sense that it was going to replace relational databases. But then it is all a question of using the right tools for the right job. Hadoop is not suitable for all kinds of data.                                                                                                                                                         No one can ignore the many benefits of Hadoop over data warehouses - but that does not mean that data warehouses are going to become the Mainframes of the 21st century. There is a huge legacy value in data warehouses - for say, transaction processing with focused index oriented queries. Hadoop will indeed provide an alternate platform for data analysis.
  • For professionals from Java background, the next most obvious progression in career is that of a Hadoop Developer or Administrator. Hadoop-Java is the most in-demand IT skill in the tidal wave of big data.
  • For professionals from ETL background, learning hadoop is the next logical step as they can use a combination of data loading tools like Flume and Sqoop along with Pig and Hive for analysis.
  • For professionals from DBA background or with expertise in SQL, learning hadoop can prove to be highly beneficial as it helps professionals translate their SQL skills for analysis using HiveQL (similar to that of SQL -key tool used for by hadoop developers for analysis). If we look at LinkedIn statistics, there is a downswing of 4% in profiles that have SQL but there is an upswing of 37% with profiles that have hadoop skill.

Hardware Requirements to Learn Hadoop

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-

1) Intel Core 2  Duo/Quad/hex/Octa or higher end 64 bit processor PC or Laptop (Minimum operating frequency of 2.5GHz)
2) Hard Disk capacity of 1- 4TB.
3) 64-512 GB RAM
4) 10 Gigabit Ethernet or Bonded Gigabit Ethernet

Grab the Opportunity to Learn Hadoop Now-

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.

Click here to know more about our IBM Certified Hadoop Developer course



Work on hands on projects on Big Data and Hadoop with Industry Professionals

Relevant Projects

Spark Project-Analysis and Visualization on Yelp Dataset
The goal of this Spark project is to analyze business reviews from Yelp dataset and ingest the final output of data processing in Elastic Search.Also, use the visualisation tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.

Hadoop Project for Beginners-SQL Analytics with Hive
In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.

Data Warehouse Design for E-commerce Environments
In this hive project, you will design a data warehouse for e-commerce environments.

Real-Time Log Processing in Kafka for Streaming Architecture
The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.

Hive Project - Visualising Website Clickstream Data with Apache Hadoop
Analyze clickstream data of a website using Hadoop Hive to increase sales by optimizing every aspect of the customer experience on the website from the first mouse click to the last.

Web Server Log Processing using Hadoop
In this hadoop project, you will be using a sample application log file from an application server to a demonstrated scaled-down server log processing pipeline.

Analyse Yelp Dataset with Spark & Parquet Format on Azure Databricks
In this Databricks Azure project, you will use Spark & Parquet file formats to analyse the Yelp reviews dataset. As part of this you will deploy Azure data factory, data pipelines and visualise the analysis.

Real-Time Log Processing using Spark Streaming Architecture
In this Spark project, we are going to bring processing to the speed layer of the lambda architecture which opens up capabilities to monitor application real time performance, measure real time comfort with applications and real time alert in case of security

Finding Unique URL's using Hadoop Hive
Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.

Airline Dataset Analysis using Hadoop, Hive, Pig and Impala
Hadoop Project- Perform basic big data analysis on airline dataset using big data tools -Pig, Hive and Impala.