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Big Data Analytics using Hadoop

Take your first step towards a new career in the field of Big Data. With our Big Data analytics certification course, learn how to drive better business decisions with an overview of how big data is organized, analyzed, and interpreted using Hadoop

120+
Hours
665
Learners
24x7
Online LMS
Hands-on
Exercises

120+
Hours

665
Learners

24x7
Online LMS

Hands-on
Exercises

₹ 23,000

Ask us everything about the program

Big Data Analytics using Hadoop

Overview

Lucrative Career Option

73% of organizations have already invested or plan to invest in big data.
Job Opportunities

Complete the Hadoop online training become eligible for over 1,500,000 jobs.
Who Should Attend

Beginners in analytics domain, engineering & non-engineering graduates.
Salary Packages

The average salary for an entry-level Big Data engineer is ₹5 lakhs per annum.
Expert Faculty

The Big Data certification course is taught by eminent big data experts.

Lucrative Career Option

73% of organizations have already invested or plan to invest in big data.

Job Opportunities

Complete the Hadoop online training become eligible for over 1,500,000 jobs.

Who Should Attend

Beginners in analytics domain, engineering & non-engineering graduates.

Salary Packages

The average salary for an entry-level Big Data engineer is ₹5 lakhs per annum.

Expert Faculty

The Big Data certification course is taught by eminent big data experts.

About Course

Are you interested in increasing your knowledge in the Big Data landscape and becoming a certified Big Data professional? Most modern businesses now have access to massive amounts of data which they are extensively using to guide their decision-making process. And Hadoop, one of the most popular open-source Big Data framework has made big data analysis easier and more accessible - increasing its potential to transform the world!

Manipal ProLearn’s course in Big Data Analytics using Hadoop will help you to understand the A to Z of Big Data and Hadoop analytics. You’ll also be able to go into the depth of other advanced Big Data technologies such as SPARK, Storm, and Kafka etc. A complete understanding of these technologies would enable you to work as a Big Data engineer and explore the world of analytics & data sciences.

What skills you learn

After completing the Big Data Analytics using Hadoop online training, you’ll be considered as a strong and competent Big Data engineer. The big data analytics with Hadoop course will help you to:

Understand what is Big Data and the sources of Big Data.
Appreciate the need for a platform like Hadoop.
Overview of the technological landscape of Big Data.
Demonstrate the ability to quickly perform ad-hoc analysis of Big Data (structured and unstructured).
Overcome the limitations of standalone tools like Excel & R.

Who Should Attend this course

Big Data Analytics aspirants

Beginners in the analytics domain

Engineering graduates

Non-engineering graduates

Big Data Analytics aspirants	Beginners in the analytics domain
Engineering graduates	Non-engineering graduates

Key Features

Learn from real-life case studies

Develop analytical and decision-making skills by examining real-life case studies.

Comprehensive Course Curriculum

Learn all the fundamentals of Big Data Analytics & Hadoop through videos, case studies, reading material, and real-time simulations.

Live Streaming Data

Learn how to process live streaming data from social media platforms like Facebook, Twitter, YouTube etc.

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Course Curriculum

1.1 Introduction to BIG DATA and Hadoop

Introduction
Challenges of Processing Big Data
Distributed Systems
History of Hadoop
Hadoop Overview
Ecosystem of Hadoop
HDFS and Map Reduce Paradigm
Processing Pipeline
Big Data Technologies
Use Cases
Features of Hadoop
Summary

1.2 Hadoop Environment Setup

Introduction
Hadoop Installation and Configuration
Hive Installation and Configuration
Pig Installation and Configuration
Sqoop Installation and Configuration
Oozie Installation and Configuration
Flume Installation and Configuration
Hbase Installation and Configuration
Hue Installation and Configuration

1.3 HDFS Architecture

Introduction
HDFS Configuration Files
Data Storage in HDFS
Blocks and Splits
Metadata Files
Name Node – Demo
HDFS Data Storage – Demo
High Availability
Data Replication – Demo
Reliable Storage – Demo
HDFS Client
Data Node – Demo
HDFS Clients – Demo
HDFS Clients – Demo

1.4 HDFS Commands

Introduction
HDFS Commands
Basic HDFS Commands - Demo
Read Anatomy in HDFS
Write Anatomy in HDFS
Additional HDFS Commands - Demo
HDFS File System API
HDFS File System API - Demo
HDFS Permission Management
Permission Management – Demo
Summary

1.5 MapReduce

MapReduce 1 Architecture
MR and Traditional Approach
Architecture 1
Introduction to YARN
Architecture 2
Summary

2.1 MapReduce Programs

Introduction
Executing a MapReduce Program - Demo
Datatypes and APIs
MapReduce Concepts
Mapper – Demo
MapReduce – Demo
Combiners – Demo
Partitioners – Demo
Debug logs & Printing in MR Jobs – Demo
Path Filters – Demo
Splits – Demo
Named Output – Demo Summary
Write MapReduce Keys and Values – Demo
Identity Mappers – Demo
Identity Reducers – Demo
Counters in Hadoop
MapReduce Counters – Demo
Input and Output Formats
About MR Unit
MR Unit – Demo
Summary

2.2 MapReduce and Job Execution

Introduction
Job Flow
Job Submission
Job Initializing
Job Scheduling
Map Task Execution
Sort and Shuffle
Reduce Task Execution
Job Cleanup
Job Failure – Demo
Staggering Job – Demo
Scheduler
Summary

2.3 Hadoop Serialization and Compression

Introduction -Serialization
Uses of Serialization
Serialization Techniques
Summary
Introduction - Compression
Uses of Compression
Compression Techniques
Summary

2.4 Advanced MapReduce Programming

Introduction
Customization of Input Format APIs
Input Format and Record Readers – Demo
Distributed Cache
Distributed Cache – Demo
Map Side Joins
Sideways Joins
Map Side Joins – Demo
Reduce Side Joins
Reduce Side Joins – Demo
Sequence File Format
Sequence File Creation – Demo
Sequence File with MapReduce -Demo
Hadoop Streaming
Hadoop Streaming – Demo
Configuring Development Environment using Eclipse – Demo
Running MapReduce Jobs – Demo
Summary

2.5 Apache Hive

Introduction
Hive vs RDBMS
Hive Architecture
Hive Components
Hive Schema Model
Hive Integration with Hadoop
Hive Query Language
Transformation in Hive
Hive Database Creation - Demo
Hive Tables - Demo
Hive Queries - Demo
Advanced Hive Partitioning - Demo
Bucketing - Demo
Advanced Concepts - Demo
Manage an XML or JSON files - Demo
Use a predefined SERDE - Demo
Summary

3.1 Apache Pig

Introduction
MapReduce and Pig
Modes of Execution in Pig
Pig Client
Pig Datatypes and Operators
SQL vs Apache Pig
Pig Usage
Loading Data in Pig – Demo
Pig Dialects – Demo
Transformations in Pig – Demo
Debugging in Pig – Demo
Other capabilities in Pig - Demo

3.2 Apache Hbase

Introduction
Categories of NoSQL Databases
Hbase Evolution
Hbase vs RDBMS
Hbase Architecture
Hbase Components
Column Family
Hbase Fundamentals
Hbase Client
Basic CRUD Operation Demo
Basic CRUD Operation
Zookeeper
Zookeeper Demo
Summary

3.3 Apache Sqoop, Oozie and Hue

Introduction - Apache Sqoop
Sqoop Usage
Working with Sqoop – Demo
Advanced Sqoop
Hive Integration – Demo
Hbase Integration – Demo
Sqoop Scripts - Demo
Introduction - Apache Oozie
Oozie Client
Basic Workflow Setup
Types of Oozie Actions
Control Statements
Defining a Workflow
Run MapReduce with Oozie - Demo
Summary
Introduction - Apache Hue
Hue User Interface
Working with Hive using Hue
Working with Pig using Hue
Monitoring an Oozie Job using Hue
Apache Hue – Demo
Summary

3.4 Streaming

Introduction Summary
Apache Flume Introduction
Flume Core Components
Launch Flume
Apache Flume - Demo
Apache Spark & Storm Introduction
Storm Concepts
Spark Streaming Concepts
Deployment Architecture
Summary

3.5 Hadoop Real Time Deployment and Distribution

Introduction - Real time deployment
System architecture
Logical deployment overview
Physical deployment overview
Summary
Introduction - Big data software and tools
Streaming tools
NoSQL tools
Workflow Tools
Administration tools
Other ecosystem tools
Summary

Frequent Questions we get

Why should I take up a Manipal ProLearn course?

Manipal ProLearn, a part of Manipal Global Education Services, offers a variety of professional certification courses across Technology, Digital Marketing, Data Sciences, Project Management, and Finance domains.

Carrying forward the Manipal legacy of over six decades in education, Manipal ProLearn helps working professionals and students to enhance their skills and fast-track their careers. Manipal ProLearn has partnered with industry leaders like Google, Microsoft, AWS Educate, EY, Sandbox, Manipal Academy of Higher Education, and Chartered Institute of Management Accountants (CIMA) to provide quality courses that add to your skill set.

We have redefined learning in the professional certification program space with a wide range of course options taught by an expert faculty on an award-winning learning platform. Benchmarked against global certification standards of PMI, CIMA, PMBOK etc., our course content is designed and developed by industry experts. Not only are these certification courses good for skill enhancement, but with industry recognised certification, they are also a great value-add to one's resume. Over the last two years, more than 80,000 learners have advanced their careers with the help of our courses.

Do I have to clear any entrance (screening) test before taking up the course?

Currently, none of the courses has an entrance test. But some certifications might have their prerequisites which are mentioned on the respective course pages.

What type of support can I expect in terms of course material, assessment, evaluation, feedback, discussion forums, mentoring etc.?

Once you have enrolled in a course, you will receive a welcome e-mail and a telephonic call from our customer support team. The features offered as part of the course will be explained clearly by our representative and also will also be listed in the mail correspondence.

Besides, our Customer Support team is available between 8 AM to 8 PM every day to help students on any course related issues.

Will I be able to access the course material post-completion too?

The course material access will be active till the validity of your course which is 3 months from the date of your enrolment.

How will successful completion of the course improve my job prospects?

Manipal ProLearn gives learners an edge when it comes to employment opportunities. By partnering with industry leaders to provide quality courses, we add to your individual skill set and make you industry ready. Also, the constantly expanding list of top-end knowledge partners ensures that learners are exposed to the latest developments and trends across sectors.

What should I do if I face any issues?

In case you come across any issue, please write to us at support@manipalprolearn.com and we will be happy to assist you. For a quicker response, use your registered e-mail id to reach out to us. Our Helpdesk is also available at 1800-103-5941 (Toll-free within India) and +91-80-42515887 and it is operational between 10:00 AM and 7:00 PM IST (Monday through Saturday). All tickets will be addressed within 48 hours.

Do you have a refund policy if I am not satisfied with the course and want to withdraw? Is there a timeframe for the same?

All refund requests received by Manipal ProLearn are processed through the same gateway within 14 working days of receiving the request. For any exceptional cases where you have not received the refund amount, please write to us at support@manipalprolearn.com. We shall get back to you with an update on your refund request or valid reasons in case of rejections.

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