Big Data Analytics using Hadoop

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Overview
  • Certification
    73% of organizations have already invested or plan to invest in big data. An industry-wide recognised certificate in Big Data Analytics using Hadoop by Manipal ProLearn will make you eligible for jobs in the Big Data industry.
  • Job Opportunities
    McKinsey predicts that by 2018 there will be a shortage of 1,500,000 data experts. After completing the big data analytics using Hadoop online training, you’ll be able to find job opportunities as a big data engineer, data scientist, or a data analyst.
  • Who Should Attend
    Beginners in analytics domain /engineering graduates /non-engineering graduates /Big Data analytics aspirants
  • Salary Packages
    The average salary for an entry-level Big Data engineer is around ₹5 lakhs per annum. An experienced Big Data engineer can earn up to ₹30 lakhs per annum.
  • Expert Faculty
    The Big Data certification course is taught by some of the most eminent big data experts and analysts who have over 16 years of experience working for companies like Microsoft, HP and more.
Certification
73% of organizations have already invested or plan to invest in big data. An industry-wide recognised certificate in Big Data Analytics using Hadoop by Manipal ProLearn will make you eligible for jobs in the Big Data industry.
Job Opportunities
McKinsey predicts that by 2018 there will be a shortage of 1,500,000 data experts. After completing the big data analytics using Hadoop online training, you’ll be able to find job opportunities as a big data engineer, data scientist, or a data analyst.
Who Should Attend
Beginners in analytics domain /engineering graduates /non-engineering graduates /Big Data analytics aspirants
Salary Packages
The average salary for an entry-level Big Data engineer is around ₹5 lakhs per annum. An experienced Big Data engineer can earn up to ₹30 lakhs per annum.
Expert Faculty
The Big Data certification course is taught by some of the most eminent big data experts and analysts who have over 16 years of experience working for companies like Microsoft, HP and more.
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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 MapReduce 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
Reliability and Rack Awareness
High Availability
Data Replication – Demo
Reliable Storage – Demo
HDFS Client
Data Node – Demo
HDFS Clients – Demo
Summary

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
Transformations 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 Storage
Hbase Client
Basic CRUD Operation
Basic CRUD Operation – Demo
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 Introduction - Apache Hue Hue User Interface Working with Hive using Hue Working with Pig using Hue Monitoring an Oozie Job using Hu
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 and 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

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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.

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

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The course material access will be active till the validity of your course which is 12 months from the date of your enrolment.

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