Key Features 

• This is a combo course which contains 4 courses of Hadoop:

1. Hadoop Developer Training
2. Hadoop Analyst Training
3. Hadoop Administration Training
4. Hadoop Testing Training

• 70 hours of High-Quality in-depth Video E-Learning Sessions
• 90 hours of Lab Exercises
• Intellipaat Proprietary VM for Lifetime and free cloud access for 6 months for performing exercises.
• 70% of extensive learning through Hands-on exercises , Project Work , Assignments and Quizzes
• The training will prepare you for Cloudera Big Data Hadoop Certification: CCA Spark and Hadoop Developer, CCAH as well as learners can learn how to work with Hortonworks and MapR Distributions
• 24*7 Lifetime Support with Rapid Problem Resolution Guaranteed
• Lifetime Access to Videos, Tutorials and Course Material
• Guidance to Resume Preparation and Job Assistance
• Step -by- step Installation of Software
• Course Completion Certificate from Intellipaat

• About Hadoop Training Course

  It is an all-in-one Big Data and Hadoop course designed to give a 360-degree overview of Apache Hadoop Architecture and its implementation on real-time projects. The major topics of Big Data Certification training include Hadoop and its Ecosystem, Apache Hadoop Architecture, core concepts of Hadoop MapReduce and HDFS (Hadoop File system), Introduction to HBase Architecture, Hadoop Cluster Setup, Apache Hadoop Administration and Maintenance. The course further includes advanced modules like Flume, Oozie, Impala, Zookeeper, Hue, Hbase and Spark.

  Learning Objectives

  After completion of this bigdata and Hadoop training, you will be able to:

  • Gain in-depth understanding of Big Data and Hadoop concepts
  • Excel in the concepts of Hadoop big data architecture and Hadoop Distributed File System (HDFS)
  • Implement HBase and MapReduce Integration
  • Understand Apache Hadoop 2.7 Framework and  Architecture
  • Learn to write complex Hadoop MapReduce programs in both MRv1 and Mrv2
  • Design and develop applications of big data using Hadoop Ecosystem
  • Set up Hadoop infrastructure with single and multi-node clusters using Amazon ec2 (CDH4)
  • Monitor a Hadoop cluster and execute routine administration procedures
  • Learn ETL connectivity with Hadoop big data, ETL tools, real-time case studies
  • Learn advanced big data technologies, write Hive and Apache Pig Scripts and work with Sqoop
  • Perform bigdata and analytics using Yarn
  • Schedule jobs through Oozie
  • Master Impala to work on real-time queries on Hadoop
  • Deal with Hadoop component failures and discoveries
  • Optimize Hadoop cluster for the best performance based on specific job requirements
  • Learn to work with complex, big data analytics tools in real-world applications and make use of Hadoop file System (like Google File System (GFS)
  • Derive insight into the field of Data Science and advanced data analytics
  • Gain insights into real-time processes happening in several big data companies
  • Work on a real-time project on Big Data Analytics and gain hands-on Big Data and Hadoop Project Experience

  Big Data and Hadoop Project Work

  1. Project – Working with Map Reduce, Hive, Sqoop

  Problem Statement – It describes that how to import MySQL data using Sqoop and querying it using hive and also defines how to run the word count Mapreduce job.

  2. Project – Work on Movie lens data for finding top records

  Data – Movie Lens data set

  Problem Statement – It includes:

  • Write a MapReduce program to find the top 10 movies from the u.data file
  • Create the same top 10 movies using PIG by loading u.data into pig
  • Create the same top 10 movies using HIVE by loading u.data into HIVE

  3. Project – Hadoop big data Yarn Project – End to End PoC

  Problem Statement – It includes:

  • Import Movie data
  • Append the data
  • How to use Sqoop commands to bring the data into the hdfs
  • End to End flow of transaction data
  • How to process the real word data or huge amount of data using MapReduce program movie etc.

  4. Project – Partitioning Tables

  Problem Statement – It describes about the parting and How to perform partitioning. It includes:

  • Manual Partitioning
  • Dynamic Partitioning
  • Bucketing

  5. Project – Sales Commission

  Data – Sales

  Problem Statement – In this Hadoop project, we calculate the commission according to the sales.

  6. Project – Connecting Pentaho with Hadoop Ecosystem (including Hadoop distributed file system, MapReduce and advanced big data analytics models)

  Problem Statement – It includes:

  • Quick Overview of ETL and BI
  • Configuring Pentaho to work with Hadoop Distribution
  • Loading data into Hadoop cluster
  • Transforming bigdata into Hadoop cluster
  • Extracting data from Hadoop Cluster

  7. Project – Multinode Cluster Setup

  Problem Statement – It includes following actions:

  • Hadoop Multi Node Cluster Setup using Amazon ec2 – Creating 4 node cluster setup
  • Running Map Reduce Jobs on Cluster

  8. Project – Hadoop Testing using MR

  Problem Statement – It describes that how to test map reduce codes with MR unit.

  9. Project – Hadoop Weblog Analytics

  Data – Weblogs

  Problem Statement – The goal is to enable the participants to have a feel of the actual data sets in a production environment and how to load the data into a Hadoop cluster using various techniques. Once data is loaded, the next goal is to perform basic analytics on this data. Further, the projects in this Hadoop and big data certification training will be very helpful for passing the Professional Certification exam on Hadoop and advanced data analytics.

  Recommended Audience

  • Programming Developers and System Administrators
  • Project managers eager to learn new techniques of maintaining large data
  • Bi Data Hadoop Developers eager to learn other verticals like Hadoop Testing, Hadoop Analytics, Hadoop Administration
  • Experienced working professionals aiming to become Big Data Analysts
  • Mainframe Professionals, Architects & Testing Professionals
  • Graduates, undergraduates and working professionals eager to learn the latest Big Data technology

  Prerequisites:

  Some prior experience on any Programming Language would be good. Basic commands knowledge of UNIX, SQL scripting. Prior knowledge of Apache Hadoop is not required.

  Why Take Big Data Hadoop Training?

  • Hadoop is a combination of online running applications on a very huge scale built of commodity hardware; a must-have Big Data technology.
  • It is handled by Apache Software Foundation and helpful in handling and storing huge amounts of data in cost-effective manner.
  • To learn Hadoop and its ecosystem and work on real-time applications of bigdata, a professional training from Industry Experts is considered a must-have.
  • Top Big Data Analytics companies like Google, Yahoo, Apple, eBay, Facebook and many others are hiring skilled professionals capable of handling Big Data.
  • Experts in Big Data Hadoop can manage complete data-based operations in big data and analytics companies .
  • This Big Data Hadoop training online provides hands-on exercises on End-to-End POC using Yarn or Hadoop that can prepare you for Professional Hadoop Certification 2.
  • You will be equipped with advanced MapReduce exercises including examples of Big data companies like Facebook, Sentiment Analysis, LinkedIn shortest path algorithm, Inverted indexing.