Big Data technology 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
Growth of Digital Data
Challenges of Processing Big Data
Introduction to Distributed Systems
Data Intensive Computations and Parallelism
History of Hadoop
Hadoop Overview
Ecosystem of Hadoop
HDFS and MapReduce Paradigm
Job Processing Pipeline
Big Data Technology Landscape
Use Cases
Features of Hadoop

1.2 HDFS Architecture

Introduction to HDFS
Cluster View of HDFS
Data Storage in HDFS
Blocks and Splits
Metadata File
Name node demo
HDFS data storage demo
Reliability and Rack Awareness
High Availability
HDFS Federation
Data Replication - Demo
HDFS Client
HDFS Clients - Demo

1.3 HDFS Operations

Introduction
HDFS commands
Basic HDFS commands demo
Read anatomy in HDFS
Write anatomy in HDFS
Additional HDFS commands demo
HDFS permission management
HDFS permission management demo -Part 1
HDFS permission management demo -Part 2

2.1 Architecture of Map-Reduce

Introduction
Traditional approach
Overview of map reduce (MR1)
System architecture of map reduce (MR1)
Introduction to YARN
Map-Reduce job execution in YARN (MR2/Hadoop 2.x)

2.2 Map-Reduce job execution

Introduction
Job flow
Job submission
Job initialization
Job scheduling
Map task execution
Sort and shuffle
Reduce task execution
Job clean-up
Scheduler

3.1 Apache Pig

Introduction
Map Reduce and PIG
Modes of execution in PIG
Pig client
Data types in PIG
Operators in PIG
Pig Usage
Loading data into PIG demo
Pig dialects
Transformations in PIG demo
Debugging in PIG demo
Other capabilities in PIG demo

3.2 Real Time Deployment and Distribution

Real time deployment introduction
System architecture
Logical deployment overview
Physical deployment overview
Real time deployment summary
Big data software and tools introduction
Streaming tools
NoSQL tools
Administration tools
Other ecosystem tools
Big data software and tools summary

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