Big Data Hadoop Certification Training

Big data Hadoop training offers you to master concepts of Hadoop framework and preparing for Big data certification. In this online certification training, we will learn components of Hadoop ecosystem such as Hadoop 2.7, Map reduces, HDFS, Pig, Impala, Flume, Apache spine etc. It also helps in implementing real-life projects in banking, telecom, social media etc.

You will learn:
  • Master fundamentals of Hadoop.
  • Setup Pseudo node and multi-node on Amazon EC2.
  • Learn spark, Spark SQL, streaming, Date graph X, RDD etc.
  • Practice real-life projects.
  • Writing Applications using Hadoop certification.
  • Complete and understanding of Big data analytics.
Who should take this course?
  • Experienced working professional.
  • Project managers.
  • Project developer and system administrator.
  • Graduates or undergraduates who are eager to learn big data techniques.
  • Business Intelligence, Data warehousing, and analytical professional.
  • No pre-requisite for taking this certification. Only basics of UNIX, SQL and java would be great to learn big data.

Course Preview

1.0 Introduction to Big Data and Hadoop
  1. Introduction to Big Data and Hadoop
  2. Objectives
  3. Need for Big Data
  4. Three Characteristics of Big Data
  5. Characteristics of Big Data Technology
  6. Appeal of Big Data Technology
  7. Handling Limitations of Big Data
  8. Introduction to Hadoop
  9. Hadoop Configuration
  10. Apache Hadoop Core Components
  11. Hadoop Core Components—HDFS
  12. Hadoop Core Components—MapReduce
  13. HDFS Architecture
  14. Ubuntu Server—Introduction
  15. Hadoop Installation—Prerequisites
  16. Hadoop Multi-Node Installation—Prerequisites
  17. Single-Node Cluster vs. Multi-Node Cluster
  18. MapReduce
  19. Characteristics of MapReduce
  20. Real-Time Uses of MapReduce
  21. Prerequisites for Hadoop Installation in Ubuntu Desktop 12.04
  22. Hadoop MapReduce—Features
  23. Hadoop MapReduce—Processes
  24. Advanced HDFS–Introduction
  25. Advanced MapReduce
  26. Data Types in Hadoop
  27. Distributed Cache
  28. Distributed Cache (contd.)
  29. Joins in MapReduce
  30. Introduction to Pig
  31. Components of Pig
  32. Data Model
  33. Pig vs. SQL
  34. Prerequisites to Set the Environment for Pig Latin
  35. Summary
1.1 Hive HBase and Hadoop Ecosystem Components
  1. Hive, HBase and Hadoop Ecosystem Components
  2. Objectives
  3. Hive—Introduction
  4. Hive—Characteristics
  5. System Architecture and Components of Hive
  6. Basics of Hive Query Language
  7. Data Model—Tables
  8. Data Types in Hive
  9. Serialization and Deserialization
  10. UDF/UDAF vs. MapReduce Scripts
  11. HBase—Introduction
  12. Characteristics of HBase
  13. HBase Architecture
  14. HBase vs. RDBMS
  15. Cloudera—Introduction
  16. Cloudera Distribution
  17. Cloudera Manager
  18. Hortonworks Data Platform
  19. MapR Data Platform
  20. Pivotal HD
  21. Introduction to ZooKeeper
  22. Features of ZooKeeper
  23. Goals of ZooKeeper
  24. Uses of ZooKeeper
  25. Sqoop—Reasons to Use It
  26. Sqoop—Reasons to Use It (contd.)
  27. Benefits of Sqoop
  28. Apache Hadoop Ecosystem
  29. Apache Oozie
  30. Introduction to Mahout
  31. Usage of Mahout
  32. Apache Cassandra
  33. Apache Spark
  34. Apache Ambar
  35. Key Features of Apache Ambari
  36. Hadoop Security—Kerberos
  37. Summary
1.2 Quiz
  1. Quiz

Why Big data And Hadoop?
  • Real-time fraud detection.
  • Web display advertising, call-center optimization.
  • Social media Analytics.
  • Simple analytics techniques are not capable of handling large volumes of data. so big data helped in handling in a timely manner. BigData and Hadoop are the new Analytical processing techniques and made the analysis possible.
  • There are many online certification courses like Edureka certification and Microsoft Hadoop certification.
  • Once you are successful in the project you will be awarded ass Edureka or Microsoft Big data and Hadoop certificate.
  • There are also discussion forums for any queries.


1) How do you benefit?
  • It is one-one session.
  • You will learn how to use Hadoop Big data in Microsoft Azure.
  • On the successful course completion, you will get the certificate.
2) Course cost?
  • The cost of the course is 165 USD.
3) Preparation:
  • There is no exam guide to preparation. The best way to prepare is hand on experience on big data techniques like Hadoop and spark.