Big Data and Hadoop

An Online course designed to Maximize your Hadoop Skills in the field of Big Data Analytics.

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About The Course

Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Hadoop Cluster- Single and multi node, Hadoop 2.0, Flume, Sqoop, Map-Reduce, PIG, Hive, Hbase, Zookeeper, Oozie etc. will be covered in the course.

Course Objectives

After the completion of the 'Big Data and Hadoop' Course at Edureka, you should be able to:


1. Master the concepts of Hadoop Distributed File System and MapReduce framework

2. Setup a Hadoop Cluster

3. Understand Data Loading Techniques using Sqoop and Flume

4. Program in MapReduce (Both MRv1 and MRv2)

5. Learn to write Complex MapReduce programs

6. Program in YARN (MRv2)

7. Perform Data Analytics using Pig and Hive

8. Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing

9. Have a good understanding of ZooKeeper service

10. New features in Hadoop 2.0 -- YARN, HDFS Federation, NameNode High Availability

11. Implement best Practices for Hadoop Development and Debugging

12. Implement a Hadoop Project

13. Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience

Who should go for this course?

This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course.

Pre-requisites

Some of the prerequisites for learning Hadoop include hands-on experience in Core Java and good analytical skills to grasp and apply the concepts in Hadoop. We provide a complimentary course "Java Essentials for Hadoop" to all the participants who enroll for the Hadoop Training. This course helps you brush up your Java skills needed to write Map Reduce programs.

Project Work

Towards the end of the Course, you will be working on a live project which will be a large dataset and you will be using PIG, HIVE, HBase and MapReduce to perform Big Data analytics. The final project is a real life business case on some open data set. There is not one but a large number of datasets which are a part of the Big Data and Hadoop Program.

Here are some of the data sets on which you may work as a part of the project work:

Twitter Data Analysis : Twitter data analysis is used to understand the hottest trends by dwelling into the twitter data. Using flume data is fetched from twitter to Hadoop in JSON format. Using JSON-serde twitter data is read and fed into HIVE tables so that we can do different analysis using HIVE queries. For eg: Top 10 popular tweets etc.

Stack Exchange Ranking and Percentile data-set : Stack Exchange is a place where you will find enormous data from multiple websites of Stack Group (like: stack overflow) which is open sourced. The place is a gold mine for people who wants to come up with several POC and are searching for suitable data-sets. In there you may query out the data you are interested in which will contain more than 50,000 odd records. For eg: You can download StackOverflow Rank and Percentile data and find out the top 10 rankers.

Loan Dataset : The project is designed to find the good and bad URL links based on the reviews given by the users. The primary data will be highly unstructured. Using MR jobs the data will be transformed into structured form and then pumped to HIVE tables. Using Hive queries we can query out the information very easily. In the phase two we will feed another dataset which contains the corresponding cached web pages of the URL's into HBASE. Finally the entire project is showcased into a UI where you can check the ranking of the URL and view the cached page.

Data -sets by Government: These Data sets could be like Worker Population Ratio (per 1000) for persons of age (15-59) years according to the current weekly status approach for each state/UT.

Machine Learning Dataset like Badges datasets : Such dataset is for system to encode names, for example +/- label followed by a person's name.

NYC Data Set: NYC Data Set contains the day to day records of all the stocks. It will provide you with the information like opening rate, closing rate, etc for individual stocks. Hence, this data is highly valuable for people you have to make decision based on the market trends. One of the analysis which is very popular and can be done on this data set is to find out the Simple Moving Average which helps them to find the crossover action.

Weather Dataset : It has all the details of weather over a period of time using which you may find out the highest, lowest or average temperature.

In addition, you can choose your own dataset and create a project around that as well.

Why learn Big Data and Hadoop?

Big Data! A Worldwide Problem ?

According to Wikipedia, "Big data is a collection of large and complex data sets which becomes difficult to process using on-hand database management tools or traditional data processing applications." In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, It is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success!

The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop, which is not less than a panacea for all those companies working with BIG DATA in a variety of applications has become an integral part for storing, handling, evaluating and retrieving hundreds or even petabytes of data.

Apache Hadoop! A Solution for Big Data!

Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!

Some of the top companies using Hadoop:

The importance of Hadoop is evident from the fact that there are many global MNCs that are using Hadoop and consider it as an integral part of their functioning, such as companies like Yahoo and Facebook! On February 19, 2008, Yahoo! Inc. established the world's largest Hadoop production application. The Yahoo! Search Webmap is a Hadoop application that runs on over 10,000 core Linux cluster and generates data that is now widely used in every Yahoo! Web search query.

Facebook, a $5.1 billion company has over 1 billion active users in 2012, according to Wikipedia. Storing and managing data of such magnitude could have been a problem, even for a company like Facebook. But thanks to Apache Hadoop! Facebook uses Hadoop to keep track of each and every profile it has on it, as well as all the data related to them like their images, posts, comments, videos, etc.

Opportunities for Hadoopers!

Opportunities for Hadoopers are infinite - from a Hadoop Developer, to a Hadoop Tester or a Hadoop Architect, and so on. If cracking and managing Big Data is your passion in life, then think no more and Join Edureka's Hadoop Online course and carve a niche for yourself! Happy Hadooping!

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