Course Overview

Hadoop is an Apache development that stores and processes Big Data. Hadoop stores big data in a dispersed manner, and its tools are also used to perform parallel data processing over HDFS (Hadoop Distributed File Systems). Therefore, becoming a professional in Big Data Analytics on Hadoop will be of utmost use to any professional in the field of Big Data.

Organisations have realised the benefits of Big Data Analytics and there is now a huge demand for Big Data and Hadoop professionals. According to Forbes, the Big Data and Hadoop market is expected to reach $99.31B by 2022, growing at a CAGR of 42.1% from 2015.

Companies are looking for Big data & Hadoop experts with the knowledge of Hadoop, and best practices for HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop & Flume.

This Big Data Analytics on Hadoop Training course is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop and its associated components. It will be a steppingstone in your Big Data journey, and you will also get the opportunity to work on various big data case studies.

Can beginners benefit from this ‘Big Data Analytics on Hadoop Training’ course? Absolutely. Hadoop is one of the leading-edge technological frameworks that is being widely used for big data.

Taking your first step towards big data is really challenging, which is why we believe you should become acquainted with the basics before applying Big Data concepts at your workplace.

This Zoe’s Big Data Hadoop training course will empower you with the in-depth knowledge and level of training professionals require for Big Data Hadoop certifications as well as to perform Big Data management tasks efficiently.

Course Objectives

Upon completing this Big Data Hadoop training course successfully, participants will be able to:

• Understand Big Data Hadoop
• Be proficient with Hadoop, HDFS, Map Reduce, Sqoop, Impala, Apache Pig, Hive and ZooKeeper
• Sit for Big Data Hadoop certification examinations
• Gain real-world skills required for Big Data roles in IT companies
• Learn the fundamentals of Hadoop and YARN and write programs using them
• Set up pseudo-node and multi-node clusters on Amazon EC2 HDFS, MapReduce, Hive, Pig, Oozie, Sqoop, Flume, ZooKeeper and HBase
• Perform Hadoop administration activities like cluster managing, monitoring, administration and troubleshooting
• Configure ETL tools like Pentaho/Talend to work with MapReduce, Hive, Pig, etc.
• Use Hadoop testing applications using MRUnit and other automation tools
• Work with Avro data formats
• Carry out real projects using Hadoop and Apache Spark
• Gain in-depth knowledge of Big Data and Hadoop including HDFS (Hadoop Distributed File System), YARN (Yet Another Resource Negotiator) & MapReduce
• Obtain comprehensive knowledge of various tools that fall in Hadoop Ecosystem like Pig, Hive, Sqoop, Flume, Oozie, and HBase
• Understand the capability to ingest data in HDFS using Sqoop & Flume, and analyse large datasets stored in the HDFS
• Study projects which are diverse in nature covering various data sets from multiple domains such as banking, telecommunication, social media, insurance, and e-commerce
• Benefit from learning with a Hadoop expert throughout the program to learn industry standards and best practices

Training Methodology

This is an interactive Big Data Hadoop training program and will consist of the following training approaches:

• Lectures
• Seminars & Presentations
• Group Discussions
• Assignments
• Case Studies & Functional Exercises

Similar to all our courses, this program also follows the ‘Do-Review-Learn-Apply’ model.

Organisational Benefits

Companies who send in their employees to participate in this Big Data Hadoop course can benefit in the following ways:

• Give your employees the ability to manage large data volumes using the latest tools
• Provide your workforce with flexible and cost-effective professional development opportunities
• Analyse case studies in this domain and be able to apply successful techniques in your organisation
• Comprehend the principles and practice of Big Data and the context in which this operates

Personal Benefits

Professionals who participate in this Big Data Hadoop training course can benefit in the following ways:

• Be up and running in the most demanding professional skills
• Progress in your career in the Big Data domain
• Benefit from a structured training with the latest curriculum as per current industry requirements and best practices
• Work on numerous practical Big Data projects using different Big Data and Hadoop tools
• Obtain the guidance of a Hadoop expert who is currently working in the industry on real-world Big Data projects and troubleshooting day-to-day challenges while implementing them

Who Should Attend?

This Big Data Hadoop training course would be suitable and useful for:

• Senior IT Professionals
• Testing professionals
• Mainframe professionals
• Software Architects
• Programming Developers and System Administrators
• Experienced working professionals and Project Managers
• Business Intelligence, Data Warehousing and Analytics Professionals
• ETL and Data Warehousing Professionals
• Data Engineers
• Data Analysts & Business Intelligence Professionals
• Database Administrators and other DB professionals

Course Outline

MODULE 1: BIG DATA

• Big Data Introduction
• Big Data Concept
• Big Data Benefits
• Data Storage & Analysis
• Querying data
• Grid computing

MODULE 2: BIG DATA HANDS-ON PRACTICE EXERCISE

• Important Note for Exercises
• Query A Public Dataset
• Creating A Dataset
• Querying A Table
• Big Table Instance
• Pub-Sub

MODULE 3: HADOOP

• Hadoop Introduction
• Hadoop Features
• HDFS Architecture
• HDFS Components
• HDFS Client
• HDFS Components
• HDFS Client creating new file
• Rack Description
• HDFS Write Operation
• Selection of Data Nodes & Node Distance
• Serialisation
• HDFS Blocks
• HDFS Caching & Failover
• HDFS Federation
• HDFS High Availability
• Hadoop Archive files
• Hadoop Releases
• Hadoop 2.0 features

MODULE 4: HADOOP EXERCISES

• Creating Cluster
• HUE HDFS File Browser
• HDFS File Browser 2
• Cloud SQL Instance
• Data Store Query
• Google Storage

MODULE 5: MAP REDUCE

• Map Reduce Introduction
• Map Reduce Phases
• Job Tracker
• Anatomy of Map Reduce Program
• Map Reduce Data Types
• Resource Manager Failure
• Submit Job
• HUE Job Designer
• HUE METASTORE MANAGER

MODULE 6: YARN

• YARN
• YARN Processing

MODULE 7: Apache HIVE

• HIVE
• HIVE Basics
• HIVE Architecture
• HIVE – Practice Exercise
• HIVE Query

MODULE 8: Apache PIG

• Apache PIG Introduction
• PIG Modes
• Comparison of PIG, HIVE, Map Reduce
• PIG

MODULE 9: IMPALA

• Data Ingestion
• Query Editors
• Components of Impala Server
• Impala Catalogue Service
• Job Designer
• IMPALA – Practice Exercise
• HUE IMPALA Query

MODULE 10: SQOOP

• Sqoop
• Sqoop Import Export

MODULE 11: UBUNTU

• Installation of Apache Hadoop 2.7.3 on Ubuntu
• Troubleshooting Guidelines

MODULE 12: CONFIGURATION MANAGEMENT

• Cluster Size Specifications
• Master Node Scenario
• Network Topology
• Cluster Setup & Installation
• Configuration Management
• HDFS Data Integrity
• Cycle of Big Data Management
• Big Data in the Cloud