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 Master Big Data tools like Spark, Storm, MongoDB and Cassandra

 Take a quantum leap in your career with the specialization course

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We are offering hadoop training on IBM Tools

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Some words about Headstar Technologies

What we do?

Headstar Technologies is the leading learning solutions and professional services provider in India. Headstar Technologies is focused on meeting the growing need for Information and Communication Technology (ICT) expertise in both global and local markets. Providing its clients with IT Training, Corporate Training, Software development, Web Development and Consultancy Services. Headstar Technologies enables its clients to accelerate their business growth through more effective use of ICT in their respective industry.It is the best IBM BP.

Course Objectives

This course, developed specifically for the business analyst will teach how to capture structured, semi-structured and unstructured data from several different data source types using IBM InfoSphere BigInsights and then do manipulations and analysis on the gathered data. This course will focus on using the Graphical User Interface of InfoSphere BigInsights to collect, manipulate, analyze, view and export data.

About the Technology

IBM® InfoSphere® BigInsights™ is an analytics platform, based on open source Apache H doop, for analyzing massive volumes of unconventional data in its native format. The software enables advanced analysis and modeling of diverse data, and supports structured, semi-structured and unstructured content to provide maximum flexibility.

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Our BIG DATA HADOOP Training

LIVE PROJECT TRAINING

The Big Data Hadoop Architect Masters Program is intended to impart an in-depth training in big data technologies like Hadoop, Spark, Scala, MongoDB/Cassandra, Kafka, Impala, and Storm. The whole program is an organized learning way prescribed by driving industry specialists and guarantees that you change into a specialist Hadoop Architect.

The program starts with Big Data Hadoop and Spark engineer courses which give a strong establishment in Big Data Hadoop innovation and proceeds onward to Apache Spark and Scala to give you an inside and out comprehension of continuous preparing. Finally, you will get an introduction to the concepts of NoSQL database technology, and you can choose between Apache Cassandra and Mongo DB. We have included Apache Storm, Kafka, and Impala as electives to help you gain a further edge.

The program provides access to 100+ live instructor-led classrooms, 90+ hours of self-paced video content, 7+ industry-based projects to be practiced on CloudLabs/Virtual machines, 10+ simulation exams, a community moderated by experts, and other resources that ensure you follow the optimal path to your dream role of a Big Data Hadoop architect.

The Masters program is intended to confer an ability in big data technologies like Hadoop, Spark, Scala, MongoDB/Cassandra, Kafka, Storm, and Impala. The learning way guarantees that the members ace the different parts of Hadoop environment like Hadoop 2.7, MapReduce, Pig, Hive, Impala, HBase, Sqoop and so forth., and learn constant preparing in Spark, Spark SQL, Spark spilling, GraphX programming, and Shell scripting flash. The course also includes NoSQL database technology like Cassandra & MongoDB. As electives, the learning way involves Storm, Impala, and Kafka, which are extra ability sets to guarantee you turn into a Hadoop champion.

In addition to being responsible for planning and designing next generation big-data systems, Hadoop Architects also manage large scale development and deployment of Hadoop applications.With Big Data giving information and energy to any organization that knows how to bridle it, Big Data Hadoop Architects have turned into the basic connection amongst business and technology. With the increasing appropriation of Big Data and Hadoop in the course of the most recent couple of years, Big Data Hadoop draftsmen are in extraordinary request, and are among the most generously compensated experts in the IT industry.

CloudLab is a cloud-based Hadoop condition to guarantee bother free execution of the considerable number of hands-on project work. As CloudLab is a pre-configured real world-like Hadoop setup, you would avoid these potential glitches that appear during a set up through a virtual Machine:

  • Installation and system compatibility issues
  • Difficulties in configuring systems
  • Issues with Rights and authorizations
  • Network slowdown and failure
  • Single machine capacity instead of clusters

CloudLab projects would be done on cloud- based Hadoop groups running with respect to Hadoop 2.711. You will be able to access CloudLab from Headstar LMS (Learning Management System).

Please Note – CloudLab access is available only for Big Data Hadoop Developer course and will be available throughout the access period of the course.

Big Data Hadoop Architect is a highly desirable career goal for those seeking to fast-track their career in the Hadoop industry. With the quantity of Big Data profession openings on the ascent, taking after parts will profit most from this learning way:-

  • Software Developers, Testers
  • Software Architects
  • Examination Professionals
  • Data Management Professionals
  • Data warehouse Professionals
  • Project Managers
  • Centralized computer Professionals
  • Graduates seeking to construct a vocation in Big Data Hadoop.

Our awesome features

Audience

MBA & Engineering – Faculty members.

Pre-requisites

Data analysis skills or equivalent knowledge.

Course Materials provided

Student Manual
Course ware in PDF format
Slide Deck (presentation format)

Assignment

This course includes Demos, and Tasks as exercises for participants. Case Studies and success stories are provided to help participants with better insight to business application.

Lab Setup Guide

Lab setup Guide is provided detailing the system pre-requisites, installation guidelines and details of setups to be followed for configuration requirement (if any)

Course Completion & Certification

On successful completion of the course participants will be provided with training completion certificate.

Our BIG DATA HADOOP CLOUDERA Training

LIVE PROJECT TRAINING

This training enables you to build complete, unified Big Data applications combining batch, streaming, and interactive analytic on all their data. With Spark, developers can write sophisticated parallel applications to execute faster and better decisions and real-time actions, applied to a wide variety of use cases, architectures, and industries.

The program starts with Big Data Hadoop and Spark engineer courses which give a strong establishment in Big Data Hadoop innovation and proceeds onward to Apache Spark and Scala to give you an inside and out comprehension of continuous preparing. Finally, you will get an introduction to the concepts of NoSQL database technology, and you can choose between Apache Cassandra and Mongo DB. We have included Apache Storm, Kafka, and Impala as electives to help you gain a further edge.

CURRICULUM

UNDERSTANDING BIG DATA AND HADOOP

 

  • Understand What Is Big Data
  • Analyze Limitations And Solutions Of Existing Data Analytics Architecture
  • Understand What Is Hadoop And Its Features
  • Hadoop Ecosystem
  • Understand Hadoop 2.x Components
  • Perform Read And Write In Hadoop
  • Understand Rack Awareness Concept

 

HADOOP ARCHITECTURE AND HDFS

 

  • Run Hadoop In Different Cluster Nodes
  • Implement Basic Hadoop Commands On Terminal
  • Prepare Hadoop 2 Configuration Files Analyze The Parameters In It.
  • Implement Password-less Ssh On Hadoop Cluster
  • Analyze Dump Of A Mapreduce Program
  • Implement Different Data Loading Techniques

 

HADOOP MAPREDUCE FRAMEWORK – I

  • Analyze Different Use-cases Where Mapreduce Is Used
  • Differentiate Between Traditional Way And Mapreduce Way
  • Learn About Hadoop 2.x Mapreduce Architecture And Components
  • Understand Execution Flow Of Yarn Mapreduce Application
  • Implement Basic Mapreduce Concepts
  • Run A Mapreduce Program

 

HADOOP MAPREDUCE FRAMEWORK – II

  • Analyze Mapreduce Job Submission Flow
  • Implement Combiner And Partitioner In Mapreduce
  • Understand Mapreduce Codes In Details
  • Code In Mapreduce For A Given Problem Statement
  • Understand Input Splits Concepts In Mapreduce
  • Module 5– Advance Mapreduce
  • Implement Counter In Mapreduce
  • Numerical Summarizations
  • Counting With Counters
  • Top K Records
  • Distinct Records
  • Total Order Sorting
  • Reduce Side Join
  • Replicated Join
  • Implement Distributed Cache Concept In Mapreduce
  • Customizing Input And Output In Hadoop
  • Implement Custom Input Format In Mapreduce
  • Implement Sequence Input Format In Mapreduce
  • Implement Xml Input Format In Mapreduce

INTRODUCTION TO CLOUDERA AND UNDERSTANDING PIG

  • Pig Features And Programming Structure
  • Pig Running Modes
  • Pig Components And Data Models
  • Basics Operations In Pig
  • Udf In Pig

 

UNDERSTANDING HIVE

  • Hive And Its Use Cases
  • Hive Vs. Pig
  • Hive Architecture And Components
  • Primitive And Complex Type In Hive
  • Data Models In Hive
  • Query Efficiency Measures
  • Partitioning
  • Bucketing
  • Hive Script And Hive Udf

 

UNDERSTANDING SQOOP AND FLUME

  • Implement Flume Job To Download Data From Twitter
  • Implement Flume Job To Download Data From Other Sources
  • Implement Sqoop To Import Table From Rdbms Into Hdfs.
  • Implement Sqoop To Import All Tables From Rdbms Into Hdfs.
  • Implement Sqoop To Import Table From Rdbms Into Hive.
  • Implement Sqoop To Import Schema And Tables Details Rdbms.
  • Implement Sqoop To Export Data To Rdbms (insert And Update Mode)
  • Implement Sqoop To Generate Java Classes Which Encapsulate And Interpret Imported Records

 

INTRODUCTION TO NOSQL AND WORKING WITH OOZIE

  • Understand Oozie
  • Schedule Job In Oozie
  • Implement Oozie Workflow
  • Implement Oozie Coordinator

 

PROJECT DISCUSSIONS

What People Are Saying About Headstar technologies

Meet our happy clients and find why our Agency is the preferred choice.

  • There is highly qualified and experinced faculty. The training is done on cloud and HADOOP. The overall training is good. The services provided are also good. And it is an happy experience here.

    Chirag Patel

  • I have been learning hadoop for about 3 weeks. My trainer is Chaitanya sir. He puts a lot of effort in practical sessions and assignments which helps a lot in understanding the fundamentals of hadoop. So far the experience with ibm has been good.

    Sumit Balhara

  • The faculty and management is quite good. Hadoop learning seems quite easy. Chaitanya sir is teaching quite well.

    Prashant Mani

  • he facilities and teaching are quite good. I can understand hadoop in a very easy way. Chaitanya sir is teaching very well.

    Shilpi Rani

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+91- 8510827111/222/888

info@headstartechnologies.com