Why should I take this certification?

Big data analysis is a trending & highly valuable skill, and it is the fastest growing technology in the world. This certification will take you from the basic level to the advanced level of Big Data Hadoop & help you become a successful Hadoop Developer, Administrator, Data Scientist Professional etc in the field of Big Data. It will teach you to apply Big Data Hadoop techniques to solve interesting real-world data related challenges. This course will cover extensive data science projects & the techniques of data acquisition, transformation and predictive analytics to solve real world problems. The certification tests the candidates on various areas in Big Data and Apache Hadoop.

Knowledge of object -oriented programming and Java programming language is pre-requisite for the certification.

The certification is not approved by, accredited by, nor in any way endorsed by, the ASF (Apache Software Foundation).

Study & Learn

  • What Data Science is
  • Apache Hadoop
  • HDFS
  • MapReduce
  • Hbase
  • Hive
  • Yarn & Pig
  • Sqoop & Flume
  • Hadoop Cluster Management

How will I benefit from this certification?

The course is designed for professionals aspiring to make a career in Big Data and Hadoop Framework. Students, Software Professionals, Analytics Professionals, ETL developers, Project Managers, Architects, and Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation on Big Data Industry can also opt for this course. With 1.8 trillion gigabytes of structured and unstructured data in the world, and the volume doubling every two years, the need for big data analysis and business intelligence has never been greater. It adds up to an incredible need for Hadoop professionals who understand how to develop, process and manage half of world's data on Hadoop. Build game-changing Big Data Applications on Hadoop and future-proof your career.

Companies that hire Hadoop Professionals

With 1.8 trillion gigabytes of structured and unstructured data in the world, and the volume doubling every two years, the need for big data analysis and business intelligence has never been greater. It adds up to an incredible need for Hadoop professionals who understand how to develop, process and manage half of world's data on Hadoop. Vskills Certified candidates in Big Data & Hadoop will find Job opportunities in Companies like IBM India, JP Morgan Chase, Capgemini, Accenture etc.

Table of Contents




Big Data and Apache Hadoop Sample Questions


Big Data and Apache Hadoop Mock Test


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1. Big Data
1.1. Big Data Definition
1.2. Big Data Types
1.3. Big Data Source
1.4. Big Data Challenges
1.5. Big Data Benefits
1.6. Big Data Applications
1.7. Netflix Application

2. Apache Hadoop
2.1. Introduction
2.2. Advantages & Disadvantages
2.3. History of Hadoop Project
2.4. Need for Hadoop
2.5. Hadoop Architecture
2.6. RDBMS vs Hadoop
2.7. Vendor Comparison
2.8. Hardware Recommendations
2.9. Hadoop Installation

3.1. Basics (Blocks, Namenodes and Datanodes)
3.2. HDFS Architecture
3.3. Data Read and Write Process
3.4. HDFS Permissions
3.5. Data Replication
3.6. HDFS Accessibility
3.7. HDFS Filesystem Operations
3.8. HDFS Interfaces
3.9. Heartbeats
3.10. Rack Awareness
3.11. distcp

4. MapReduce
4.1. MapReduce Basics
4.2. MapReduce Work Flow
4.3. MapReduce Framework
4.4. Hadoop Data Types
4.5. MapReduce Internals
4.6. Job Formats
4.7. Debugging and Profiling
4.8. Distributed Cache
4.9. Combiner Functions
4.10. Streaming
4.11. Counters, Sorting and Joins

5.1. YARN Infrastructure
5.2. ResourceManager
5.3. ApplicationMaster
5.4. NodeManager
5.5. Container

6. Pig
6.1. Pig Architecture
6.2. Installation and Modes
6.3. Grunt and Pig Script
6.4. Pig Latin Commands
6.5. UDF and Data Processing Operator

7. HBase
7.1. HBase Architecture
7.2. HBase Installation
7.3. HBase Configuration
7.4. HBase Schema Design
7.5. HBase Commands
7.6. MapReduce Integration
7.7. HBase Security

8. Sqoop and Flume
8.1. Sqoop
8.2. Flume

9. Hive
9.1. Hive Architecture
9.2. Hive shell
9.3. Hive Data types
9.4. HiveQL

10. Workflow
10.1. Apache Oozie

11. Hadoop Cluster Management
11.1. Cluster Planning
11.2. Installation and Configuration
11.3. Testing
11.4. Benchmarking
11.5. Monitoring

12. Administration
12.1. dfsadmin, fsck and balancer
12.2. Logging
12.3. Data Backup
12.4. Add and removal of nodes

13. Security
13.1. Authentication
13.2. Data Confidentiality
13.3. Configuration

14. NextGen Hadoop
14.1. HDFS HA
14.2. HDFS Federation

“Exam scheduling to be done through user account” / “Exam once scheduled cannot be cancelled”
Date of Examination
Examination Time
01:00 PM - 02:00 PM
02:30 PM - 03:30 PM
04:00 PM - 05:00 PM
05:30 PM - 06:30 PM
10:00 AM - 11:00 AM
11:30 AM - 12:30 PM

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