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Big Data Hadoop Certification Training

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CertHippo's Big Data Hadoop Training Course is curated by Hadoop industry experts, and it covers in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume and Sqoop. Throughout this online instructor-led Hadoop Training, you will be working on real-life industry use cases in Retail, Social Media, Aviation, Tourism and Finance domain using Certhippo's Cloud Lab. This course is to prepare you for success in the role of Big Data Developer. Learn how various components of Hadoop ecosystem fit into the Big Data processing Lifecycle.

Why this course ?

Hadoop Market is expected to reach $99.31B by 2022 at a CAGR of 42.1% -Forbes.Average Salary of Big Data Hadoop Developers is $135k (Indeed.com salary data). Worldwide revenues for Big Data and Business Analytics solutions will reach $260 billion in 2022 with a CAGR of 11.9% as per International Data Corporation (IDC). Big Data is the fastest growing and the most promising technology for handling large volumes of data for doing data analytics. This Big Data Hadoop training will help you be up and running in the most demanding professional skills Hadoop is very popular in many leading MNCs like Honeywell, Marks & Spencer, Royal Bank of Scotland, and British Airways.

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Instructor-led Sessions

30hrs of Online Live Instructor-led Classes. Weekend class:10 sessions of 3 hours each and Weekday class:15 sessions of 2 hours each.

Real-life Case Studies

Live project based on any of the selected use cases, involving Big Data Analytics.


Each class will be followed by practical assignments which can be completed before the next class.

Lifetime Access

You get lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.

24 x 7 Expert Support

We have 24x7 online support team available to help you with any technical queries you may have during the course.


Towards the end of the course, you will be working on a project. AddiLearncertifies you as an Big Data and Hadoop Expert based on the project.


We have a community forum for all our customers wherein you can enrich their learning through peer interaction and knowledge sharing.

This Cirthippo's Big Data Hadoop Certification training course is designed to make you a certified Big Data developer by providing you rich hands-on training on Hadoop ecosystem and best practices about HDFS, MapReduce, HBase, Hive, Pig, Oozie, Sqoop. This course is stepping stone to your Big Data journey and you will get the opportunity to work on a Big data Analytics project after selecting a data-set of your choice. You will get Certhippo Hadoop certification after the project completion.

The Certhippo hadoop training is designed to help you become a top big data Hadoop developer. During this course, our expert instructors will train you to- 

  • Master the concepts of HDFS and MapReduce framework
  • Understand Hadoop 2.x Architecture
  • Setup Hadoop Cluster and write Complex MapReduce programs
  • Learn data loading techniques using Sqoop and Flume
  • Perform data analytics using Pig, Hive and YARN
  • Implement HBase and MapReduce integration
  • Implement Advanced Usage and Indexing
  • Schedule jobs using Oozie
  • Implement best practices for Hadoop development
  • Understand Spark and its Ecosystem
  • Learn how to work in RDD in Spark
  • Work on a real life Projects on Big Data Analytics

Big Data & Hadoop Market is expected to reach $99.31B by 2022 growing at a CAGR of 42.1% from 2015 - Forbes

McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts - Mckinsey Report

Avg salary of Big Data Hadoop Developers is $135k - Indeed.com Salary Data.

Big Data is the fastest growing and the most promising technology for handling large volumes of data for doing data analytics. This Big Data Hadoop training will help you be up and running in the most demanding professional skills.That is there is a great opportunity for all the IT Professionals. 

Here are the some IT Professional groups, who are continuously moving into Big data domain for enjoying the benefits:

  • Developers and Architects
  • BI /ETL/DW professionals
  • Senior IT Professionals
  • Testing professionals
  • Mainframe professionals
  • Freshers

Hadoop practitioners are the highest paid IT professionals today with salaries ranging till $85K (source: indeed job portal), and the market demand for them is growing very fastly.

You can check a blog related to Why Choose Hadoop As a Career? Also, once your Hadoop training is over, you can check the Top interview questions related Certhippo blog.

Real-time Analytics is the new market buzz and having Apache Spark skills is a highly preferred and demanding domain after the Hadoop training. 

As such, there are no pre-requisites for learning Hadoop. If you have Knowledge of Core Java and SQL then it will be more beneficial for you, but certainly not a mandate. If you wish to brush-up Core-Java skills, CertHippo offer you a complimentary self-paced course, i.e. "Java essentials for Hadoop" when you enroll in Big Data Hadoop Certification course.

Your system should have 4GB RAM and i3 processor. In case, your system falls short of these requirements, we can provide you remote access to our Hadoop Cluster.

We will help you to setup Certhippo's Virtual Machine in your System with local access. The detailed installation guides are provided in the LMS for setting up the environment. In case your system doesn't meet the pre-requisites e.g. 4GB RAM, you will be provided remote access to the Certhippo cluster for the practicals. For any doubt, the 24*7 support team will promptly assist you.Certhippo Virtual Machine can be installed on Mac or Windows machine.

      After completion of the course, you will work on a live project where you will be using PIG, HIVE, HBase and MapReduce to perform Big Data analytics. 
      There are industry-specific Big Data case studies that are included in our Big Data and Hadoop Certification e.g. Finance, Retail, Media, Aviation etc. which is consider for your project work:

      • Project #1: Analyze social bookmarking sites to find insights

    Industry: Social Media

    Data: There are the information gathered from bookmarking sites like reddit.com, stumbleupon.com, allow you to bookmark, review, rate, search various links on any topic. reddit.com, stumbleupon.com, etc. These data are in the XML format and keeps various links/posts URL, categories defining it and the ratings linked with it.

    Problem Statement:Analyze data in the Hadoop ecosystem:

    • Fetch the data from Hadoop Distributed File System and analyze data with the help of MapReduce, Pig and Hive to find out the top rated links based on the user comments, likes etc.
    • By the use of MapReduce, you can convert the semi-structured format (XML data) into a structured format and categorize the user rating as positive and negative for each of the thousand links.
    • Push these output HDFS and then after feed it into PIG, which partitions of the data into two parts: Category data and Ratings data.
    • Write a fancy Hive Query to analyze the data further and push the output is into relational database (RDBMS) by the use of Sqoop.
    • By using the web server running on grails/java/ruby/python that renders the result in real time processing on a website.

    • Project #2: Analysis of Customer Complaints

    Industry: Retail

    Data: These data are available on publicly, containing a few lakh observations with attributes like; CustomerId, Payment Mode, Product Details, Complaint, Location, Status of the complaint, etc.

    Problem Statement: Analyze data in the Hadoop ecosystem:

    • Get the number of complaints filed under each product
    • Get the total number of complaints filed from specific location
    • Get the list of complaints grouped by location which has no any reaction on time

    • Project #3: Tourism Data Analysis

    Industry: Tourism

    Data: The data comprises attributes like: City pair (combination of from and to), adults traveling, seniors traveling, children traveling, air booking price, car booking price, etc.

    Problem Statement:Find the following insights from the data:

    • Top 20 destinations people frequently travel: Based on the given data we can find the most popular destinations where people often travel, based on the specific initial number of trips booked for a specific destination
    • Top 20 locations from where highest number of trips start. It is based on the booked trip count
    • Top 20 high air-revenue destinations, i.e the 20 cities that generate high airline revenues for travel, so that the discount offers can be given to attract more bookings for these destinations.

    • Project #4: Airline Data Analysis

    Industry: Aviation

    Data:  The data which contains the flight details of various airlines such as: Airport id, Name of the airport, Main city served by airport, Country or territory where airport is stationed, Code of Airport, Decimal degrees, Hours offset from UTC, Timezone, etc.

    Problem Statement:Analyze the airlines' data to:

    • Find list of airports operating in the country
    • Find the list of airlines having zero stops
    • List of airlines operating with code share
    • Which country (or) territory has the most number of airports
    • Find out the list of active airlines in the United States

    • Project #5: Analyze Loan Dataset

    Industry: Banking and Finance

    Data: Publicly available dataset which contains all the details of loans issued, including the current loan status (Current, Late, Fully Paid, etc.) and latest payment information.

    Problem Statement:

    • Find out the number of cases as per location and categorize the count with respect to reason for taking loan and display the average risk score.

    • Project #6: Analyze Movie Ratings

    Industry: Media

    Data: These data are available publicly from sites like rotten tomatoes, IMDB, etc.

    Problem Statement:Analyze the ratings of movies by different users:

    • Get the user who has highest rated of movies
    • Get the user who has lowest rated of movies
    • Get the count of total number of movies rated by user who belongs to a specific occupation
    • Get the number of underage users

    • Project #7: Analyze YouTube data

    Industry: Social Media

    Data: It is all about the YouTube videos and contains attributes such as: VideoID, Uploader, Age, Category, Length, views, ratings, comments, etc.

    Problem Statement:

    • Identify the top 5 categories in which most videos are uploaded, the top 10 rated videos, and the top 10 most viewed videos.

    Except from these there are some twenty more use-cases to choose:

Market data Analysis

    • Twitter Data Analysis

Learning Objectives : In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, the common Hadoop ecosystem components, Hadoop Architecture, HDFS, Anatomy of File Write and Read, how MapReduce Framework works.

Topics : Big Data, Limitations and Solutions of existing Data Analytics Architecture, Hadoop, Hadoop Features, Hadoop Ecosystem, Hadoop 2.x core components, Hadoop Storage: HDFS, Hadoop Processing: MapReduce Framework, Hadoop Different Distributions.

Learning Objectives :In this module, you will learn the Hadoop Cluster Architecture, Important Configuration files in a Hadoop Cluster, Data Loading Techniques, how to setup single node and multi node hadoop cluster. Topics-Hadoop 2.x Cluster Architecture - Federation and High Availability, A Typical Production Hadoop Cluster, Hadoop Cluster Modes, Common Hadoop Shell Commands, Hadoop 2.x Configuration Files, Single node cluster and Multi node cluster set up Hadoop Administration.

Learning Objectives :In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will understand concepts like Input Splits in MapReduce, Combiner & Partitioner and Demos on MapReduce using different data sets. Topics-MapReduce Use Cases, Traditional way Vs MapReduce way, Why MapReduce, Hadoop 2.x MapReduce Architecture, Hadoop 2.x MapReduce Components, YARN MR Application Execution Flow, YARN Workflow, Anatomy of MapReduce Program, Demo on MapReduce. Input Splits, Relation between Input Splits and HDFS Blocks, MapReduce: Combiner & Partitioner, Demo on de-identifying Health Care Data set, Demo on Weather Data set.

Learning Objectives :In this module, you will learn Advanced MapReduce concepts such as Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format and XML parsing. Topics : Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format, Xml file Parsing using MapReduce.

Learning Objectives : In this module, you will learn about Pig, types of  Pig, use cases of Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, PIG running modes, PIG UDF, Pig Streaming, Testing PIG Scripts. Demo on healthcare dataset.

Topics : About Pig, MapReduce Vs Pig, Pig Use Cases, Programming Structure in Pig, Pig Running Modes, Pig components, Pig Execution, Pig Latin Program, Data Models in Pig, Pig Data Types, Shell and Utility Commands, Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Specialized joins in Pig, Built In Functions ( Eval Function, Load and Store Functions, Math function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution ( PIG macros and Pig Parameter substitution ), Pig Streaming, Testing Pig scripts with Punit, Aviation use case in PIG, Pig Demo on Healthcare Data set.

Learning Objectives : This module will help you in understanding Hive concepts, Hive Data types, Loading and Querying Data in Hive, running hive scripts and Hive UDF.

Topics : Hive Background, Hive Use Case, About Hive, Hive Vs Pig, Hive Architecture and Components, Metastore in Hive, Limitations of Hive, Comparison with Traditional Database, Hive Data Types and Data Models, Partitions and Buckets, Hive Tables(Managed Tables and External Tables), Importing Data, Querying Data, Managing Outputs, Hive Script, Hive UDF, Retail use case in Hive, Hive Demo on Healthcare Data set.

Learning Objectives : In this module, you will learn Advanced Hive concepts such as UDF, Dynamic Partitioning, Hive indexes and views, optimizations in hive. You will also learn in-depth knowledge of HBase, HBase Architecture, running modes and its components.

Topics : Hive QL: Joining Tables, Dynamic Partitioning, Custom Map/Reduce Scripts, Hive Indexes and views Hive query optimizers, Hive : Thrift Server, User Defined Functions, HBase: Introduction to NoSQL Databases and HBase, HBase v/s RDBMS, HBase Components, HBase Architecture, Run Modes & Configuration, HBase Cluster Deployment.

Learning Objectives : This module will cover Advanced HBase concepts. We will see demos on Bulk Loading , Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.

Topics : HBase Data Model, HBase Shell, HBase Client API, Data Loading Techniques, ZooKeeper Data Model, Zookeeper Service, Zookeeper, Demos on Bulk Loading, Getting and Inserting Data, Filters in HBase.

Learning Objectives : In this module you will learn Spark ecosystem and its components, how scala is used in Spark, SparkContext. You will learn how to work in RDD in Spark. Demo will be there on running application on Spark Cluster, Comparing performance of MapReduce and Spark.

Topics : What is Apache Spark, Spark Ecosystem, Spark Components, History of Spark and Spark Versions/Releases, Spark a Polyglot, What is Scala?, Why Scala?, SparkContext, RDD.

Learning Objectives : In this module, you will learn how it work on multiple Hadoop ecosystem components together in a Hadoop implementation to solve Big Data problems.Big Data Hadoop Certification Trainingdoop Talend integration.

Topics : Flume and Sqoop Demo, Oozie, Oozie Components, Oozie Workflow, Scheduling with Oozie, Demo on Oozie Workflow, Oozie for MapReduce, PIG, Hive, and Sqoop, Combine flow of MR, PIG, Hive in Oozie, Oozie Co-ordinator, Oozie Commands, Oozie Web Console, Hadoop Project Demo, Hadoop Integration with Talend.

"You will never lose any lecture. You can choose either of the two options:

  • View the recorded session of the class available in your LMS.
  • You can attend the missed session, in any other live batch."

Certhippois committed to provide you an awesome learning experience through world-class content and best-in-class instructors. We will create an ecosystem through this training, that will enable you to convert opportunities into job offers by presenting your skills at the time of an interview. We can assist you in resume building and also share important interview questions once you are done with the training. However, please understand that we are not into job placements.

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrolment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in the class.

All the instructors at Certhippo are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are experts in their domain and are trained by Certhippo for providing an awesome learning experience.

    • Once you are successfully completed your project (Reviewed by the Certhippo experts), you will be awarded with Certhippo's Big Data and Hadoop certificate.
    • Certhippo certification has industry recognition and we are the preferred training partner for many MNCs e.g.Cisco, Ford, Mphasis, Nokia, Wipro, Accenture, IBM, Philips, Citi, Ford, Mindtree, BNYMellon etc. Please be ensured.