Big Data Hadoop Analyst Training Course Online Course

Big Data Hadoop Analyst Training Course

All levels
English

Course Description

Big Data Hadoop Analyst 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. This training course will give you the right skills to deploy various tools and techniques to be a Hadoop Analyst working with Big Data. Big Data Analyst offers a wide range of scope for the job seekers, data analytics is considered as a backbone of the company, thus, the employees handling the related department should have working knowledge on SQL or basic LINUX commands, the database, SQL, and query language for databases. The Big Data Hadoop Analyst Professional Program insights on installing, updating and maintaining MongoDB environment. Make them understand Data Volume, Data Evolution, Velocity of Data, MapReduce and the procedure of developing distributed processing of large data sets across clusters of computers and administering Hadoop.

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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
How the open source ecosystem of big data tools addresses challenges not met by traditional RDBMSs
Hive and Impala syntax and data formats, including functions and subqueries
Create and use partitions and different file formats. Combining two or more datasets using JOIN or UNION, as appropriate
Process and analyze semi-structured and unstructured data. Techniques for optimizing Hive and Impala queries
How to determine whether Hive, Impala, an RDBMS, or a mix of these is best for a given task
Using Apache Hive and Apache Impala to provide SQL access to data
Create, modify, and delete tables, views, and databases; load data; and store results of queries
What analytic and windowing functions are, and how to use them. Store and query complex or nested data structures
Extending the capabilities of Hive and Impala using parameters, custom file formats and SerDes, and external scripts

Covering Topics

Introduction to Apache Hadoop Fundamentals

Introduction to Apache Hive and Impala

Querying with Apache Hive and Impala

Common Operators and Built-In Functions

Data Storage

Data Storage and Performance

Working with Multiple Datasets

Analytic Functions and Windowing

Complex Data

Analyzing Text

Apache Hive Optimization

Apache Impala Optimization

Extending Apache Hive and Impala

Choosing the Best Tool for the Job

Curriculum

  Live Lecture 
·       The Motivation for Hadoop

·       Hadoop Overview

·       Data Storage: HDFS

·       Distributed Data Processing: YARN, MapReduce, and Spark

·       Data Processing and Analysis: Pig, Hive, and Impala

·       Database Integration: Sqoop

·       Other Hadoop Data Tools

·       Exercise Scenario Explanation

·       Practical Exercise

  Live Lecture 
·       What Is Hive?

·       What Is Impala?

·       Why Use Hive and Impala?

·       Schema and Data Storage

·       Comparing Hive and Impala to Traditional Databases

·       Use Cases

·       Practical Exercise

  Live Lecture 
·       Databases and Tables

·       Basic Hive and Impala Query Language Syntax

·       Data Types

·       Using Hue to Execute Queries

·       Using Beeline (Hive's Shell)

·       Using the Impala Shell

·       Practical Exercise

  Live Lecture 
·       Operators

·       Scalar Functions

·       Aggregate Functions

·       Practical Exercise

  Live Lecture 
·       Creating Databases and Tables

·       Loading Data

·       Altering Databases and Tables

·       Simplifying Queries with Views

·       Storing Query Results

·       Practical Exercise

  Live Lecture 
·       Partitioning Tables

·       Loading Data into Partitioned Tables

·       When to Use Partitioning

·       Choosing a File Format

·       Using Avro and Parquet File Formats

·       Practical Exercise

  Live Lecture 
·       UNION and Joins

·       Handling NULL Values in Joins

·       Advanced Joins

·       Practical Exercise

  Live Lecture 
·       UNION and Joins

·       Handling NULL Values in Joins

·       Advanced Joins

·       Practical Exercise

  Live Lecture 
·       Using Common Analytic Functions

·       Other Analytic Functions

·       Sliding Windows

·       Practical Exercise

  Live Lecture 
·       Complex Data with Hive

·       Complex Data with Impala

·       Practical Exercise

  Live Lecture 
·       Using Regular Expressions with Hive and Impala

·       Processing Text Data with SerDes in Hive

·       Sentiment Analysis and n-grams

·       Practical Exercise

  Live Lecture 
·       Understanding Query Performance

·       Bucketing

·       Hive on Spark

·       Practical Exercise

  Live Lecture 
·       How Impala Executes Queries

·       Improving Impala Performance

·       Practical Exercise

  Live Lecture 
·       Custom SerDes and File Formats in Hive

·       Data Transformation with Custom Scripts in Hive

·       User-Defined Functions

·       Parameterized Queries

·       Practical Exercise

  Live Lecture 
·       Custom SerDes and File Formats in Hive

·       Data Transformation with Custom Scripts in Hive

·       User-Defined Functions

·       Parameterized Queries

·       Practical Exercise

  Live Lecture 
·       Comparing Hive, Impala, and Relational Databases

·       Which to Choose?

·       Conclusion

·       Practical Exercise

Frequently Asked Questions

A basic knowledge in any programming language is beneficial but not necessary.

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.