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⚡ Overview

Brilliance IT Techno is the best Big Data training institute in Jaipur. Big data is a collection of large datasets that cannot be processed using conventional computing systems. Big data is not just a data; instead it has become a complete subject, which includes various tools, methods and frameworks. Big data is very much in demand in Jaipur as there are many Competitive Advantages of Big Data in Business. Big Data is large chunk of raw data that is collected, stored and analyzed through various means which can be utilized by organizations to increase their effectiveness and take better decisions.

Big data means a collection of large datasets that cannot be processed using simple programming models. It has become a complete subject, which includes various tools, methods and frameworks.

Organizations are learning that important forecasts can be made by sorting through and analyzing Big Data. As more than 80% of this data is “unstructured”, it must be formatted in a way that makes it suitable for data mining and the analysis.

Hadoop is fundamental platform for structuring big data. It is an Apache open source framework written in java that permits distributed processing of large datasets across collections of computers with the help of simple programming models. It provides massive storage for any type of data, huge processing power and the capability to handle virtually limitless parallel tasks or jobs.

Open-source software framework from Apache

Inspired by: Google mapreduce , GFS (Google file system)

HDFS

MapReduce

Some More

Benefits of Big Data Hadoop Training

Upskilling in Big Data and Analytics field is a smart career decision. According to Allied Market Research, the global Hadoop market will reach $84.6 Billion by 2021 and there is a shortage of 1.4-1.9 million Hadoop data analysts in the U.S. alone. Here are a selection of Hadoop specialist opportunities in your area:

Big Data Architect:

Annual Salary : Min - ₹10L / Max - ₹30L

Hiring Companies : Amazon, Hewlett Packard Enterprise, accenture, Visa

Big Data Engineer:

Annual Salary : Min - ₹4.2L / Max - ₹13L

Hiring Companies : Amazon, Linkedin, American Express, Microsoft, MasterCard

Big Data Developer:

Annual Salary : Min - ₹3.5L / Max - ₹16L

Hiring Companies : Barclays, Cognizant, IBM, CISCO, VMWARE

⚡ About Big Data Hadoop

Hadoop was invented by Doug Cutting, the creator of Apache Lucene, the widely used text search library. Following are the major events that led to the creation of the stable version of Hadoop that's available.

  • 2003 - Google launches project Nutch to handle billions of searches and indexing millions of web pages.
  • Oct 2003 - Google releases papers with GFS (Google File System)
  • Dec 2004 - Google releases papers with MapReduce
  • 2005 - Nutch used GFS and MapReduce to perform operations
  • 2006 - Yahoo! created Hadoop based on GFS and MapReduce (with Doug Cutting and team)
  • 2007 - Yahoo started using Hadoop on a 1000 node cluster
  • Jan 2008 - Apache took over Hadoop
  • Jul 2008 - Tested a 4000 node cluster with Hadoop successfully
  • 2009 - Hadoop successfully sorted a petabyte of data in less than 17 hours to handle billions of searches and indexing millions of web pages.
  • Dec 2011 - Hadoop releases version 1.0
  • Aug 2013 - Version 2.0.6 is available
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This is the age of Hadoop. There is a plethora of job opportunities in the field of Hadoop. Some companies are even modernizing their search engines with the support of Hadoop technology. As a result, they are looking forward to hiring more people with Hadoop skills to support the search process. Then again, some companies are also hiring people with work experience on Open Stack with Hadoop as one of the major necessity.

Companies that are hiring individuals having expertise in Big Data Hadoop training, now and in the future are looking for various roles including:

  • Product managers,
  • Database administrators,
  • Engineers and professionals with operating skills,
  • Software testers,
  • Senior Hadoop developers,
  • Hadoop developers.
  • Team leads

Further, individuals should enroll for Big Data Hadoop training in noida as Big Data Hadoop is everywhere and it will provide them:

  • Better career
  • Better salary
  • Big companies hiring
  • Better job opportunities
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BRILLIANCE is the best Training, Development Company active in Jaipur, & Upcomming in Various big cities providing Big Data Hadoop training to students and other working professionals. BRILLIANCE provides highly skilled and experienced professional experts to train students and make them strong for their professional career.

Its Big Data Hadoop training course contents are designed according to the current Industry Standards. So, its best opportunity for the students to join the Big Data Hadoop training to grasp the technical knowledge and have the large number of job prospects with them. BRILLIANCE provide Big Data Hadoop training as tutorialS. Big Data Hadoop training with best lab facility. BRILLIANCE gives short term as well as long term Big Data Hadoop training. BRILLIANCE is also providing Big Data Hadoop training to Corporate Employees and Professionals on end-to- end enterprise solutions.

Students choose BRILLIANCE for its Big Data Hadoop training in comparison to other companies because of its following features:
  • BRILLIANCE provide one year membership card to every student of BRILLIANCE enrolling for Big Data Hadoop training.
  • BRILLIANCE have highly skilled trainers to train students in Big Data Hadoop training.
  • It provides flexible timings of Big Data Hadoop training according to the need of the students.
  • Placement assistance in international and multinational IT companies after successful completion of Big Data Hadoop training.
  • Six months Industrial Big Data Hadoop training with expert and experienced faculty members.
  • BRILLIANCE gives best lab facility and best infrastructure and opportunity to students to work on live projects.
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The top companies using BIG DATA HADOOP are:
  • Yahoo ( One of the biggest user & more than 80% code contributor to Hadoop).
  • Facebook
  • Netflix
  • Amazon
  • Adobe
  • Ebay
  • Alibaba
  • Google
  • Twitter
  • IBM
  • Linkedin

These top level companies demand professionals having expertise in Big Data Hadoop and reward them with superb packages and good career growth. Hence, students should join BRILLIANCE for Big Data Hadoop training to fulfill their career demand

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The Motivation & Limitation for Hadoop:
  • Problems with Traditional Large-Scale Systems.
  • Why Hadoop & Hadoop Fundamental Concepts.
  • History of Hadoop with Hadoop problems.
  • Advantages and Disadvantages of Hadoop.
  • Available version Hadoop 2.x & 3.x
  • Available Distributions of Hadoop (Cloudera, Hortonworks).
  • Hadoop Projects & Components.
  • The Hadoop Distributed File System (HDFS).
Hadoop Ecosystem & Cluster:

Hadoop Ecosystem projects & Components overview.

  • HDFS – File System.
  • HBase – The Hadoop Database.
  • Cassandra – No-SQL Database.
  • Hive – SQL Engine.

Hadoop Architecture overview Cluster Daemons & Its Functions.

  • Name Node
  • Secondary Node.
  • Data Nodes
Planning Hadoop Cluster & Initial Configuration:
  • General Planning Considerations.
  • Choosing the Right Hardware.
  • Network Considerations.
  • Configuring Nodes.
  • Planning for Cluster & Its Management.
  • Types of Deployment.
  • Cloudera Manager.
Installation & Deployment of Hadoop:
  • Installing Hadoop.
  • Installation – Pig, Hive, HBase, Cassandra etc.
  • Specifying the Hadoop Configuration.
  • Performing Initial HDFS Configuration.
  • Performing Initial YARN and MapReduce Configuration.
  • Hadoop Logging & Cluster Monitoring.
Load Data and Run Application:
  • Load Data from External Sources with Flume.
  • Load Data from Relational Databases with Sqoop.
  • Rest Interfaces.
  • Best Practices for Importing Data.
Manage, Maintain, Monitor, and troubleshoot of cluster:
  • General System Monitoring.
  • Monitoring Hadoop Clusters.
  • Common Troubleshooting Hadoop Clusters.
  • Common Misconfigurations.
  • Managing Running Jobs.
  • Scheduling Hadoop Jobs.
Upgrade, Rolling and Backup:
  • Cluster Upgrading.
  • Checking HDFS Status.
  • Adding and Removing Cluster Nodes.
  • Name Node Meta Data Backup.
  • Data Backup.
  • Distributed Copy.
  • Parallel Data Ingestion.

Conclusion & FAQs

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Introduction to Big Data:
  • What is RDBMS?
  • What is Big Data?
  • Problems with the RDBMS and other existing systems.
  • Requirement for the new approach.
  • Solution to the problem with huge.
  • Difference between relational databases and NoSQL type databases.
  • Need of NoSQL type databases.
  • Problems in processing of Big Data with the traditional systems.
  • How to process and store Big Data?
  • Where to use Hadoop?
Hadoop Basic Concepts:
  • What is Hadoop?
  • Why to use Hadoop?
  • Architecture of Hadoop.
  • Difference between Hadoop 1.x and Hadoop 2.x
  • What is YARN?
  • Advantage of Hadoop 2.x over Hadoop 1.x
  • Use cases for using Hadoop.
  • Components of Hadoop.
  • Hadoop Distributed File System (HDFS).
  • Map Reduce.
Hadoop Distributed File System (HDFS):
  • Components of HDFS.
  • What was the need of HDFS.
  • High Availability and Fault Tolerance.
  • Command Line interface.
  • Data Ingestions.
Hadoop Cluster:
  • Installation of Hadoop.
  • Understanding the Configuration of Hadoop.
  • Starting the Hadoop related Processes.
  • Visualization of Hadoop in UI.
  • Writing the files to the HDFS.
  • Reading the files from the Hadoop Cluster.
  • Work flow of the Job.
HIVE:
  • Introduction to HIVE.
  • Architecture of HIVE.
  • Why HIVE?
  • RDBMS Vs HIVE.
  • Introduction to HiveQL.
  • Loading data using HIVE.
  • HIVE Vs Map Reduce Coding.
  • Different functions supported in HIVE.
  • Partitioning, Bucketing in HIVE.
  • Hive Built-In Operators and Functions.
  • Why do we need Partitioning and Bucketing in HIVE?
PIG:
  • Introduction to Apache Pig.
  • Architecture of Apache Pig.
  • Why Pig?
  • RDBMS Vs Apache PIG.
  • Loading data using PIG.
  • Different Modes of execution of PIG Command.
  • PIG Vs Map Reduce coding.
  • operations in Pig.
  • Combining and Filtering Operations in pig.
HBASE:
  • What is HBASE?
  • Why HBASE is needed?
  • HBASE Architecture and Schema Design.
  • Column Oriented and Row Oriented Database.
  • HBASE Vs RDBMS.
Sqoop:
  • What is Sqoop?
  • Use Case for Sqoop?
  • Configuring Sqoop.
  • Importing and Exporting Data using Sqoop.
  • Importing data into Hive using Sqoop.
  • Code Generation using Sqoop.
  • Using Map Reduce with the Sqoop.
Flume:
  • What is Flume?
  • Architecture of Flume.
  • Why we need Flume?
  • Problem with traditional export method.
  • Configuring Flume.
  • Different Channels in Flume.
  • Importing data using Flume.
  • Using Map Reduce with the Flume.
Map Reduce Programming:
  • History of Map Reduce.
  • Flow of Map Reduce.
  • Working of Map Reduce with simple example.
  • Difference Between Map phase and Reduce phase.
  • Concept of Partition and Combiner phase in Map Reduce.
  • Submission of a Map Reduce job in Hadoop cluster and it’s completion.
  • File support in Hadoop.
  • Achieving different goals using Map Reduce programs.

Mini Project to Use Hadoop and Related Technologies on a Dataset.

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⚡ Target Audience in Big Data Hadoop

Basic knowledge of Core Java and SQL

They Can Do.

Graduates looking to begin a career in big data analytics

They Can Do.

Data management professionals, Testing and mainframe professionals

They Can Do.

⚡ FAQs

  • What is Hadoop Map Reduce
    • For processing large data sets in parallel across a hadoop cluster, Hadoop MapReduce framework is used. Data analysis uses a two-step map and reduce process.

  • Explain what is NameNode in Hadoop?
    • NameNode in Hadoop is the node, where Hadoop stores all the file location information in HDFS (Hadoop Distributed File System). In other words, NameNode is the centrepiece of an HDFS file system. It keeps the record of all the files in the file system, and tracks the file data across the cluster or multiple machines

  • Explain what is heartbeat in HDFS?
    • Heartbeat is referred to a signal used between a data node and Name node, and between task tracker and job tracker, if the Name node or job tracker does not respond to the signal, then it is considered there is some issues with data node or task tracker

  • Explain what is sqoop in Hadoop
    • To transfer the data between Relational database management (RDBMS) and Hadoop HDFS a tool is used known as Sqoop. Using Sqoop data can be transferred from RDMS like MySQL or Oracle into HDFS as well as exporting data from HDFS file to RDBMS

  • Mention what is the data storage component used by Hadoop?
    • The data storage component used by Hadoop is HBase.

⚡ STUDENTS FEEDBACK

Abhijeet

Brilliance is the no.1 training institute in jaipur for big data Hadoop training institute for 4 Weeks ,6 weeks and 6 months training. Trainers for big data Hadoop training is more expert and cooperative as compare to another institution in jaipur & Rajasthan.

3 months

Kartik Rawat

Brilliance is the best training company and institute for big data hadoop. I am saying this because of my excellent experience with brilliance they provide globally certified big data hadoop training. If you want to learn hadoop by working on live project,then opt for Brilliance.

8 months

Girish

Brilliance IT Techno is one of the best cost-effective solutions to learn online & Offline mode study. I enrolled in their Big Data Hadoop and Android Development course

4 months

Nikhil Pal

I am impressed with the trainer's in-depth knowledge and excellent communication skills. He understood our questions and answered them very efficiently. Thanks Brilliance

2 months

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