Master the key concepts of Hadoop and Big data. Join and learn from a Big Data/Hadoop expert.

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  • Big Data Hadoop as the name implies, is an open-source utility software that helps to handle a large amount of data and possesses immense processing power. The USP of Big Data Hadoop is its ability to manage unlimited data simultaneously. Data analytics rely on the Big Data Hadoop platform because they are quite simple, fast, and flexible.
  • Our Big Data Hadoop online training at Croma Campus is crafted by our team of experts to cater to the individual needs of the learners. It infuses detailed knowledge of Big Data Hadoop features like HDFS, YARN, Hive, Map Reduce, Pig, Spark, HBase, Sqoop, Flume, Oozie, and Hive, etc, to its learners. Get the benefit to work on real-life industry cases through our extensive Big Data Hadoop Online Training.
  • Big Data Hadoop has witnessed a surge in its demand across the IT domain. Having a requisite skillset in handling Big Data using Hadoop gives you an upper hand over others seeking to enter the IT domain. Some of the popular Big Data job titles are Big Data Hadoop – Developer, Administrator, Data Analyst, Tester, and Solution Architect.

Big Data Hadoop Online Training

About-Us-Course

  • The main objective of our Big Data Hadoop training and certification program online is to make you an expert in Big Data Hadoop learning skills. Here are a few of the skills you will be learning in our training course:
    • You will get to master all the basics of Big Data Hadoop, YARN, Map Reduce, and become an expert in writing apps using the mentioned tools.

      Our Big Data Hadoop online training institute in India inculcates deep knowledge of HDFS, Sqoop, Pig, Hive, Oozie, shell scripting, Spark, Flume, Zookeeper online.

      With the leading Big data Hadoop online training in India, you will acquire a clear understanding of the Big Data Hadoop cluster and learn Big Data Hadoop analytics as well.

      Learn to create various ETL tools and know about set the pseudo nodes too.

      With the Big data Hadoop placement training online, get hands-on experience through our real-life projects and assignments.

  • According to a recent study by Indeed, the salary of a Big Data Hadoop Developer is expected to range between $119,250 to $168,250 per annum and approx. $110,000 per year for a Big Data Hadoop Admin.
  • The average salary of Big Data Hadoop professionals across the world is:
    • Big Data Hadoop Analyst - $110K

      Big Data Hadoop Administrator - $125K

      Big Data Hadoop Developers - $135K

      Big Data Hadoop Architect - $170K

  • Here are some facts about Big Data Hadoop that might provide you reliable insights about the domain:
    • Big Data Hadoop Analytics is the most desirable data analytic tool.

      It enhances the efficiency of an organization.

      Big Data Hadoop Analytic tools are utilized to get better insights into their sales and marketing facilities.

      Big data Hadoop is boosting business processes by marketing it on the social media platform.

      The requirement of certified Big data Hadoop professionals is high as there are very few skilled analytical professionals available in the market.

  • According to Mckinsey, there will be a shortfall of skilled analysts and managers in near future and hence it will be a really great opportunity for you in the desired field. Hence enroll in our Big Data Hadoop certification course and pave your way towards an enormous career opportunity.

  • There is without a doubt enormous career opportunity in the Big Data Hadoop domain:
    • Backed by our experts and real-time sessions, the Big Data Hadoop training course offers a comprehensive knowledge of Big Data Hadoop, Big Data Hadoop certifications, and the current market trends in the relevant field.

      Our course curriculum is the perfect blend of theoretical as well as practical components.

      Big Data Hadoop online training session delivers Big Data framework, Storage & Processing, Sqoop, Pig, Hive, Oozie, Shell scripting, Spark detailed sessions in a practical way so that the learners can easily grasp the subject. It also offers live sessions, provides study material, PPT, projects, etc.

      Upon completing the Big Data Hadoop certification training program, you will directly qualify for the next level certification and thereafter establish as a Big Data Hadoop expert.

  • Big Data Hadoop online training has become more and more popular over the years as most of the companies are shifting to the Big Data Hadoop system. Due to the flexible nature of Big Data Hadoop, it is able to control the overall system and store data in HDFS and supports data compression. Big Data can be installed using tools such as Map Reduce, Pig, and Hive.
  • According to a survey, it is predicted that the Big Data Hadoop market will rise up to $99.31 by 2022. There will be a shortage of certified Big Data Hadoop skilled experts around 1.6 million in the US alone. Almost every premium company has adopted the Big Data Hadoop system.
  • If you are trained in the niche technology at one of the leading Big Data Hadoop online training institute in India, you will get to learn at your own pace and comfort Zone, leverage the benefits of interactive training sessions. With Instructor-led Big Data Hadoop classes get cost-effective personalized training.
  • Needless to say that Big Data Hadoop platform seems promising and it will keep on progressing in the years to come by.

  • Big Data Hadoop online training professionals are responsible for the following job roles and responsibilities that are covered as a part of our Big Data Hadoop online training program:
    • Get proficient in conducting database modeling and development, data mining, and warehousing.

      Should be able to develop, implement and maintain Big Data solutions.

      Should be an expert in designing and deploying data platforms across multiple domains ensuring operability.

      Must have hands-on expertise in transforming data for meaningful analyses, improving data efficiency, reliability & quality, creating data enrichment, building high performance, and ensuring data integrity.

      Must have sufficient experience working with the Big Data Hadoop ecosystem (HDFS, MapReduce, Oozie, Hive, Impala, Spark, Kerberos, KAFKA, etc.).

      Must know all about Spark core, HBase or Cassandra, Pig, Yarn, SQL, MongoDB, RDBMS, DW/DM, etc.

      Need to play a crucial role in the development and deployment of innovative big data platforms for advanced analytics and data processing.

  • After completing Big Data Hadoop online training in India developer is one of the most preferred choices. Almost all companies have started accepting the Big Data ecosystem making Big Data Hadoop professionals even more alluring. Some of the top industries using and thus hiring Big Data experts are Infosys, Accenture, IBM, Wipro, TCS, Cognizant, HCL, Dell, etc.
  • Indeed, Big Data Hadoop analytics would be the best career option for you. Furthermore, the high demand for Data Analytics skills is boosting the salary for qualified professionals.

  • Since organizations have acknowledged the benefits of Big Data Hadoop online training. Hence, the demand for jobs in Big Data Hadoop is also increasing rapidly. To seize this opportunity individuals need to take proper training from our Big Data Hadoop online training institute in India and clear the certification exam expeditiously.
  • Once you complete the training program at Big Data Hadoop online training in India, you will become an authorized Developer, Administrator, Data Analyst, Tester, or Solution Architect. Thus, if you are interested to pursue your career in this field, then this is the apt time to enroll in our Big Data Hadoop placement course online and savor a remarkable career ahead.

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Plenary for Big Data Hadoop Training

TrackWeek DaysWeekendsFast Track
Course Duration 40-45 Days 7 Weekends 8 Days
Hours 1 Hrs. Per Day 2 Hrs. Per Day 6+ Hrs. Per Day
Training ModeClassroom/OnlineClassroom/OnlineClassroom/Online
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CURRICULUM & PROJECTS

Big Data Hadoop Training

  • Croma Campus offers the best Hadoop development Training in Noida with most experienced professionals. Our Instructors are working in Big Data Space and related technologies for years in MNC's.
  • We aware of industry needs and we are offering Hadoop development Training in more practical way. Our team of Hadoop trainers offers the in-classroom training with best industry practices.
  • We framed our syllabus to match with the real-world requirements for beginner level to advanced level. Our training will be handled in either weekday or weekends programme depends on participants requirements.
  • In this program you will learn:
    • Introduction to Big Data & Hadoop

      HDFS

      YARN

      Managing and Scheduling Jobs

      Apache Sqoop

      Apache Flume

      Getting Data into HDFS

      Apache Kafka

      Hadoop Clients

      Cluster Maintenance

      Cloudera Manager

      Cluster Monitoring and Troubleshooting

      Planning Your Hadoop Cluster

      Advanced Cluster Configuration

      MapReduce Framework

      Apache PIG

      Apache HIVE

      No SQL Databases HBase

      Functional Programming using Scala

      Apache Spark

      Hadoop Datawarehouse

      Writing MapReduce Program

      Introduction to Combiner

      Problem-solving with MapReduce

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  • Introduction to Big Data
    • Overview of Course

      What is Big Data

      Big Data Analytics

      Challenges of Traditional System

      Distributed Systems

  • Introduction to Hadoop
    • Components of Hadoop Ecosystem

      Commercial Hadoop Distributions

      Why Hadoop

      Fundamental Concepts in Hadoop

  • Security in Hadoop
    • Why Hadoop Security Is Important

      Hadoop’s Security System Concepts

      What Kerberos Is and How it Works

      Securing a Hadoop Cluster with Kerberos

  • Initial Setup and Configuration
    • Deployment Types

      Installing Hadoop

      Specifying the Hadoop Configuration

      Performing Initial HDFS Configuration

      Performing Initial YARN and MapReduce Configuration

      Hadoop Logging

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  • HDFS
    • What is HDFS

      Need for HDFS

      Regular File System vs HDFS

      Characteristics of HDFS

      HDFS Architecture and Components

      High Availability Cluster Implementations

      HDFS Component File System Namespace

      Data Block Split

      Data Replication Topology

      HDFS Command Line

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  • YARN
    • Yarn Introduction

      Yarn Use Case

      Yarn and its Architecture

      Resource Manager

      How Resource Manager Operates

      Application Master

      How Yarn Runs an Application

      Tools for Yarn Developers

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  • Managing and Scheduling Jobs
    • Managing Running Jobs

      Scheduling Hadoop Jobs

      Configuring the Fair Scheduler

      Impala Query Scheduling

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  • Apache Sqoop
    • Apache Sqoop

      Sqoop and Its Uses

      Sqoop Processing

      Sqoop Import Process

      Sqoop Connectors

      Importing and Exporting Data from MySQL to HDFS

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  • Apache Sqoop
    • Apache Flume

      Flume Model

      Scalability in Flume

      Components in Flume’s Architecture

      Configuring Flume Components

      Ingest Twitter Data

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  • Getting Data into HDFS
    • Data Ingestion Overview

      Ingesting Data from External Sources with Flume

      Ingesting Data from Relational Databases with Sqoop

      REST Interfaces

      Best Practices for Importing Data

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  • Apache Kafka
    • Apache Kafka

      Aggregating User Activity Using Kafka

      Kafka Data Model

      Partitions

      Apache Kafka Architecture

      Setup Kafka Cluster

      Producer Side API Example

      Consumer Side API

      Consumer Side API Example

      Kafka Connect

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  • Hadoop Clients
    • What is a Hadoop Client

      Installing and Configuring Hadoop Clients

      Installing and Configuring Hue

      Hue Authentication and Authorization

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  • Cluster Maintenance
    • Checking HDFS Status

      Copying Data between Clusters

      Adding and Removing Cluster Nodes

      Rebalancing the Cluster

      Cluster Upgrading

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  • Cloudera Manager
    • The Motivation for Cloudera Manager

      Cloudera Manager Features

      Express and Enterprise Versions

      Cloudera Manager Topology

      Installing Cloudera Manager

      Installing Hadoop Using Cloudera Manager

      Performing Basic Administration Tasks using Cloudera Manager

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  • Cluster Monitoring and Troubleshooting
    • General System Monitoring

      Monitoring Hadoop Clusters

      Common Troubleshooting Hadoop Clusters

      Common Misconfigurations

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  • Planning Your Hadoop Cluster
    • General Planning Considerations

      Choosing the Right Hardware

      Network Considerations

      Configuring Nodes

      Planning for Cluster Management

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  • Advanced Cluster Configuration
    • Advanced Configuration Parameters

      Configuring Hadoop Ports

      Explicitly Including and Excluding Hosts

      Configuring HDFS for Rack Awareness

      Configuring HDFS High Availability

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  • MapReduce Framework
    • What is MapReduce

      Basic MapReduce Concepts

      Distributed Processing in MapReduce

      Word Count Example

      Map Execution Phases

      Map Execution Distributed Two Node Environment

      MapReduce Jobs

      Hadoop MapReduce Job Work Interaction

      Setting Up the Environment for MapReduce Development

      Set of Classes

      Creating a New Project

      Advanced MapReduce

      Data Types in Hadoop

      Output formats in MapReduce

      Using Distributed Cache

      Joins in MapReduce

      Replicated Join

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  • Apache PIG
    • Introduction to Pig

      Components of Pig

      Pig Data Model

      Pig Interactive Modes

      Pig Operations

      Various Relations Performed by Developers

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  • Apache HIVE
    • Introduction to Apache Hive

      Hive SQL over Hadoop MapReduce

      Hive Architecture

      Interfaces to Run Hive Queries

      Running Beeline from Command Line

      Hive Meta Store

      Hive DDL and DML

      Creating New Table

      Data Types

      Validation of Data

      File Format Types

      Data Serialization

      Hive Table and Avro Schema

      Hive Optimization Partitioning Bucketing and Sampling

      Non-Partitioned Table

      Data Insertion

      Dynamic Partitioning in Hive

      Bucketing

      What Do Buckets Do

      Hive Analytics UDF and UDAF

      Other Functions of Hive

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  • No SQL Databases HBase
    • NoSQL Databases HBase

      NoSQL Introduction

      HBase Overview

      HBase Architecture

      Data Model

      Connecting to HBase

      HBase Shell

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  • Functional Programming using Scala
    • Basics of Functional Programming and Scala

      Introduction to Scala

      Scala Installation

      Functional Programming

      Programming with Scala

      Basic Literals and Arithmetic Programming

      Logical Operators

      Type Inference Classes Objects and Functions in Scala

      Type Inference Functions Anonymous Function and Class

      Collections

      Types of Collections

      Operations on List

      Scala REPL

      Features of Scala REPL

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  • Apache Spark
    • Apache Spark Next-Generation Big Data Framework

      History of Spark

      Limitations of MapReduce in Hadoop

      Introduction to Apache Spark

      Components of Spark

      Application of In-memory Processing

      Hadoop Ecosystem vs Spark

      Advantages of Spark

      Spark Architecture

      Spark Cluster in Real World

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  • Data warehouse in Hadoop
    • Hadoop and the Data Warehouse

      Hadoop Differentiators

      Data Warehouse Differentiators

      When and Where to Use Which

  • Augmenting Enterprise Data Warehouse
    • Introduction

      RDBMS Strengths

      RDBMS Weaknesses

      Typical RDBMS Scenario

      OLAP Database Limitations

      Using Hadoop to Augment Existing Databases

      Benefits of Hadoop

      Hadoop Trade-offs

  • Advance Programming in Hadoop
    • Advance Programming in Hadoop

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  • Writing MapReduce Program
    • A Sample MapReduce Program: Introduction

      Map Reduce: List Processing

      MapReduce Data Flow

      The MapReduce Flow: Introduction

      Basic MapReduce API Concepts

      Putting Mapper & Reducer together in MapReduce

      Our MapReduce Program: Word Count

      Getting Data to the Mapper

      Keys and Values are Objects

      What is Writable Comparable

      Writing MapReduce application in Java

      The Driver

      The Driver: Complete Code

      The Driver: Import Statements

      The Driver: Main Code

      The Driver Class: Main Method

      Sanity Checking the Job’s Invocation

      Configuring the Job with Job Conf

      Creating a New Job Conf Object

      Naming the Job

      Specifying Input and Output Directories

      Specifying the Input Format

      Determining Which Files to Read

      Specifying Final Output with Output Format

      Specify the Classes for Mapper and Reducer

      Specify the Intermediate Data Types

      Specify the Final Output Data Types

      Running the Job

      Reprise: Driver Code

      The Mapper

      The Mapper: Complete Code

      The Mapper: import Statements

      The Mapper: Main Code

      The Map Method

      The map Method: Processing the Line

      Reprise: The Map Method

      The Reducer

      The Reducer: Complete Code

      The Reducer: Import Statements

      The Reducer: Main Code

      The reduce Method

      Processing the Values

      Writing the Final Output

      Reprise: The Reduce Method

      Speeding up Hadoop development by using Eclipse

      Integrated Development Environments

      Using Eclipse

      Writing a MapReduce program

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  • Introduction to Combiner
    • The Combiner

      MapReduce Example: Word Count

      Word Count with Combiner

      Specifying a Combiner

      Demonstration: Writing and Implementing a Combiner

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  • Sorting & Searching large data sets
    • Introduction

      Sorting

      Sorting as a Speed Test of Hadoop

      Shuffle and Sort in MapReduce

      Searching

  • Performing a secondary sort
    • Secondary Sort: Motivation

      Implementing the Secondary Sort

      Secondary Sort: Example

  • Indexing data and inverted Index
    • Indexing

      Inverted Index Algorithm

      Inverted Index: Data Flow

      Aside: Word Count

  • Term Frequency - Inverse Document Frequency (TF- IDF)
    • Term Frequency Inverse Document Frequency (TF-IDF)

      TF-IDF: Motivation

      TF-IDF: Data Mining Example

      TF-IDF Formally Defined

      Computing TF-IDF

  • Calculating Word co- occurrences
    • Word Co-Occurrence: Motivation

      Word Co-Occurrence: Algorithm

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+ More Lessons

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Validate your skills and knowledge by working on industry-based projects that includes significant real-time use cases.Gain hands-on expertize in Top IT skills and become industry-ready after completing our project works and assessments.Our projects are perfectly aligned with the modules given in the curriculum and they are picked up based on latest industry standards. Add some meaningful project works in your resume, get noticed by top industries and start earning huge salary lumps right away.
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FAQ's

Croma Campus is one of the excellent Big Data Hadoop Online Training Institute in India that offers hands-on practical knowledge, practical implementation on live projects and will ensure the job with the help of Big Data Hadoop Online course, Croma Campus provides Big Data Hadoop Online Training by industrial experts, they have 8+ years working experience in top organization.

Croma Campus associated with top organizations like HCL, Wipro, Dell, BirlaSoft, Tech Mahindra, TCS, IBM, etc. make us capable to place our students in top MNCs across the globe. Our training curriculum is approved by our placement partners.

Croma Campus in India mentored more than 3000+ candidates with Big Data Hadoop Online Certification Training in India at a very reasonable fee. The course curriculum is customized as per the requirement of candidates/corporates. You will get study material in the form of E-Books, Online Videos, Certification Handbooks, Certification and 500 Interview Questions along with Project Source material.

For details information & FREE demo class, call us at 120-4155255, +91-9711526942 or write to us info@cromacampus.com
Address: – G-21, Sector-03, Noida (201301)

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