Hadoop Data Analytics Training Course Online Course

Hadoop Data Analytics Training Course

All levels
English

Course Description

Hadoop Data Analytics training course explains how to apply data analytics and business intelligence skills to Big Data. This Big Data Analytics training lays emphasis on the usage of Apache Pig, Hive, and Cloudera Impala. It will drive you through the process of developing distributed processing of large data sets across clusters of computers and administering Hadoop.The participants will learn how to handle heterogeneous data coming from different sources. This data may be structured, unstructured, communication records, log files, audio files, pictures, and videos. Organizations now have access to massive amounts of data and it’s influencing the way they operate. They are realizing in order to be successful they must leverage their data to make effective business decisions. This course will enable an Analyst to work on Big Data and Hadoop which takes into consideration the burgeoning demands of the industry to process and analyze data at high speeds.

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What you’ll learn

Live Class Practical Oriented Training
Timely Doubt Resolution
Dedicated Student Success Mentor
Certification & Job Assistance
Free Access to Workshop & Webinar
No Cost EMI Option
Explain the fundamentals of Apache Hadoop, Data ETL (extract, transform, load), data processing using Hadoop tools
Perform data management and text processing using Hive
Comparative study of MapReduce, Pig, Hive, Impala, and Relational Databases
Performing data analysis and processing complex data using Pig
Extending, troubleshooting, and optimizing Pig and Hive performance Analyze data with Impala

Covering Topics

Introduction about Big Data

Hadoop Fundamentals

Introduction to Pig

Basic Data Analysis with Pig

Processing Complex Data with Pig

Multi-Dataset Operations with Pig

Extending Pig

Pig Troubleshooting and Optimization

Introduction to Hive

Relational Data Analysis with Hive

Hive Data Management

Text Processing with Hive

Hive Optimization

Extending Hive

Introduction to Impala

Analyzing Data with Impala

Choosing the Best Tool for the Job

Curriculum

  Lecture-1. Introduction about Big Data

Live Lecture 
·       Introductions

  Lecture-2. Hadoop Fundamentals

Live Lecture 
·       The Motivation for Hadoop

·       Hadoop Overview

·       HDFS

·       MapReduce

·       The Hadoop Ecosystem

·       Lab Scenario Explanation

  Lecture-3. Introduction to Pig

Live Lecture 
·       What Is Pig?

·       Pig’s Features

·       Pig Use Cases

·       Interacting with Pig

  Lecture-4. Basic Data Analysis with Pig

Live Lecture 
·       Pig Latin Syntax

·       Loading Data

·       Simple Data Types

·       Field Definitions

·       Data Output

·       Viewing the Schema

·       Filtering and Sorting Data

·       Commonly-Used Functions

  Lecture-5. Processing Complex Data with Pig

Live Lecture 
·       Storage Formats

·       Complex/Nested Data Types

·       Grouping

·       Built-in Functions for Complex Data

·       Iterating Grouped Data

  Lecture-6. Multi-Dataset Operations with Pig

Live Lecture 
·       Techniques for Combining Data Sets

·       Joining Data Sets in Pig

·       Set Operations

·       Splitting Data Sets

  Lecture-7. Extending Pig
Live Lecture 
·       Adding Flexibility with Parameters

·       Macros and Imports

·       UDFs

·       Contributed Functions

·       Using Other Languages to Process Data with Pig

  Lecture-8. Pig Troubleshooting and Optimization
Live Lecture 
 

·       Troubleshooting Pig

·       Logging

·       Using Hadoop’s Web UI

·       Optional Demo: Troubleshooting a Failed Job with the Web UI

·       Data Sampling and Debugging

·       Performance Overview

·       Understanding the Execution Plan

·       Tips for Improving the Performance of Your Pig Jobs

  Lecture-9. Introduction to Hive
Live Lecture 
·       What Is Hive?

·       Hive Schema and Data Storage

·       Comparing Hive to Traditional Databases

·       Hive vs. Pig

·       Hive Use Cases

·       Interacting with Hive

  Lecture-10. Relational Data Analysis with Hive
Live Lecture 

·       Hive Databases and Tables

·       Basic HiveQL Syntax

·       Data Types

·       Joining Data Sets

·       Common Built-in Functions

  Lecture-11. Hive Data Management
Live Lecture 

·       Hive Data Formats

·       Creating Databases and Hive-Managed Tables

·       Loading Data into Hive

·       Altering Databases and Tables

·       Self-Managed Tables

·       Simplifying Queries with Views

·       Storing Query Results

·       Controlling Access to Data

  Lecture-12. Text Processing with Hive
Live Lecture 
·       Overview of Text Processing

·       Important String Functions

·       Using Regular Expressions in Hive

·       Sentiment Analysis and N-Grams

  Lecture-9. Introduction to Hive
Live Lecture 
·       What Is Hive?

·       Hive Schema and Data Storage

·       Comparing Hive to Traditional Databases

·       Hive vs. Pig

·       Hive Use Cases

·       Interacting with Hive

  Lecture-13. Hive Optimization
Live Lecture 
·       Understanding Query Performance

·       Controlling Job Execution Plan

·       Partitioning

·       Bucketing

·       Indexing Data

  Lecture-14. Extending Hive
Live Lecture 
·       SerDes

·       Data Transformation with Custom Scripts

·       User-Defined Functions

·       Parameterized Queries

  Lecture-15. Introduction to Impala
Live Lecture 
·       What is Impala?

·       How Impala Differs from Hive and Pig

·       How Impala Differs from Relational Databases

·       Limitations and Future Directions

·       Using the Impala Shell

  Lecture-16. Analyzing Data with Impala
Live Lecture 
·       Basic Syntax

·       Data Types

·       Filtering, Sorting, and Limiting Results

·       Joining and Grouping Data

·       Improving Impala Performance

  Lecture-17. Choosing the Best Tool for the Job
Live Lecture 
·       Comparing MapReduce, Pig, Hive, Impala, and Relational Databases

·       Which to Choose?

Frequently Asked Questions

The candidates with working experience with SQL or basic LINUX commands are ideal for this training.

The course offers a variety of online training options, including: • Live Virtual Classroom Training: Participate in real-time interactive sessions with instructors and peers. • 1:1 Doubt Resolution Sessions: Get personalized assistance and clarification on course-related queries. • Recorded Live Lectures*: Access recorded sessions for review or to catch up on missed classes. • Flexible Schedule: Enjoy the flexibility to learn at your own pace and according to your schedule.

Live Virtual Classroom Training allows you to attend instructor-led sessions in real-time through an online platform. You can interact with the instructor, ask questions, participate in discussions, and collaborate with fellow learners, simulating the experience of a traditional classroom setting from the comfort of your own space.

If you miss a live session, you can access recorded lectures* to review the content covered during the session. This allows you to catch up on any missed material at your own pace and ensures that you don't fall behind in your learning journey.

The course offers a flexible schedule, allowing you to learn at times that suit you best. Whether you have other commitments or prefer to study during specific hours, the course structure accommodates your needs, enabling you to balance your learning with other responsibilities effectively. *Note: Availability of recorded live lectures may vary depending on the course and training provider.