What are the prerequisites to learn Big Data and Hadoop?

We are going to explain all the necessary prerequisites to learning Big Data and Hadoop technologies. This article will provide enough guides to decide your career in Big Data and Analytics.

What are the prerequisites to learn Big Data and Hadoop?

Big Data and Hadoop - Complete information about the prerequisites to learn Big Data and Hadoop

In this guide we will tell you the necessary prerequisites for learning the Big Data and Hadoop technologies. You will be able to select the correct path and also find the details about important topics to learn.

Big Data and Hadoop plays major role in the growth of large scale data storage at a very high speed. It helps to process and analyze data very quickly. Social networking websites and large e-commerce portals are the major users of Big Data technologies.

So, the technological details are very in-depth and one can't learn all the technologies. Its necessary to define your path and then learn the technologies of Big Data development.

Prerequisites to learn Big Data and Hadoop

Now are giving you details about the necessary prerequisites of learning these technologies.

Linux Operating system

Hadoop is mostly installed on the Linux operating system and the preferred OS is the Ubuntu server distribution. So, you should have basics knowledge of working Linux desktop, Linux commands and editors. You should be able to install and uninstall linux package. Linux skills is must to learn Big Data and Hadoop. If you don't have any experience with Linux then gab a distribution of Ubuntu desktop, install in Virtual box and learn it.
Programming Skills

Prior experience with any programming language is very important as it helps you in understanding Hadoop programming. Based on your career path selection in Big Data you have to learn easy of difficult programming languages. Its not necessary to have programming skills but if you are a programmer you can make better career in Big Data development and Analytics.

Programming languages you should learn are:

  • Java
  • Python
  • Scala

Java Programming Language is not a strict prerequisite for learning Big Data; you can use the high level programming languages for analyzing the data. Hadoop now supports Hadoop Streaming and you can use any programming which allows you to reading through standard input and writing to a standard for programming.

Job Roles in Hadoop

  • Hadoop Architect
  • Hadoop Developer
  • Hadoop Admin
  • Hadoop Tester
  • Linux/Network/Hardware Administrator
  • Data Analyst

If you see the above job roles you will find that for some job Java is required and for others it's not.

SQL Knowledge

SQL knowledge is necessary and you should learn the SQL queries before learning the Hadoop technologies.

Apache Hive, Pig, HBase, thrift are major software packages used with the Hadoop Ecosystem and these provides SQL like query for querying the data from HDFS. So, you should learn SQL also before starting learning Hadoop and Big data. You can practice SQL query by installing MySQL Database server on your local computer.

Mathematics and Statics

You should have good understanding of mathematics and particular the statics. You should be able to solve a problem by applying mathematical formula or set of formulas. Good mathematics is necessary for predictive analysis and machine learning rule sets.

Hadoop System

Hadoop comes with Storage (HDFS, S3 etc.) and Distributed computing (MapReduce, EMR etc), so, a good Hadoop professional should learn these also.

You should learn Hadoop Big Data Platform, HBase, Hive, Storm, Spark, Pig, R, Elasticsearch, Machine learning frameworks and many more technologies to master fast growing Big Data field.

In the future Internet of Things (IoT) will be very popular and there also Big Data platform will be used for managing such a huge data set.

Big users of Big Data are banking, insurance, e-commerce, hospitality, manufacturing, marketing, advertising, social media, healthcare, transportation and scientific researches.

Big Data is growing fast and professionals must learn new technologies on time to develop innovative solutions.

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