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Big Data Hadoop Certification New York Training Course

  • Get yourself enrolled in our comprehensive, real-world projects led Hadoop Training New York Program to master the skills and tools in the Hadoop ecosystem.
  • Learn all the practical learnings around Hadoop Architecture, Apache PIG, Hive, SQOOP, Hbase, YARN, Impala, Apache Spark with Scala, and OOZIE that will help you in qualifying the competent Hadoop Certification New York and make your career a demanding one.

Know what all it takes to design and develop solutions around the Hadoop System!

Next Class Begins in 4 days - 22 Nov 2024

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Why to go for Hadoop training certification?

Let’s come across and have a close look as to why certification of Hadoop Training New York courses is a must need.

#1

Hadoop is the no. 1 Big data management Framework.

$120k+

The average Hadoop Developer salary in USA is $120,450 per year

Salesforce Growth

You Should Join Our Classes If You Are:

  • Just starting off & aren’t sure where to start from
  • In an established role but need to dive deep
  • Looking to brush up your skills & master the course
  • Willing to get better in your current or new job

$670.8 B

Global Hadoop Market is Estimated to Reach $670.8 billion by 2025.

64%

1.6K Students have successfully completed Big Data Hadoop training and now working for top MNC's

Thriving Career Opportunities - What and Where!

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Know what all it takes to design and develop solutions around the Hadoop System!

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Financial
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Hadoop Developer

Data Scientist

Hadoop Admin

Big Data Hadoop Engineer

Some Hilarious & Concealed Facts About New York City

  • The NYC public school system is the largest system in the U.S - teaching 1.1 million students under 1700 schools.
  • Most New Yorkers have more than 1 job - could be like one Hadoop job to meet their career needs & second job to reflect their passions/interests.
  • The city’s current employment rate is 96.6%. So if you have the right skills & training, your chances of employment are high.
  • New York has the highest population density of any American city and New Yorkers can speak around 800 languages.
New York is a great place to live or relocate to as it has everything you need, from delicious food to exotic locations to roam around to versatile entertainment activities to high paying jobs to all needed facilities --- which altogether are justified for a quality life.
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Instructor-led Live Online Hadoop Classes


Starting
Duration
Price

calendar-icon122 Nov

WEEKDAY - Filling Fast

6 weeks

USD 1199

USD 1019

Flat 15% Off

calendar-icon106 Dec

WEEKDAY

6 weeks

USD 1199

calendar-icon107 Dec

WEEKEND

6 weeks

USD 1199

calendar-icon120 Dec

WEEKDAY

6 weeks

USD 1199

calendar-icon103 Jan

WEEKDAY

6 weeks

USD 1199

USD 959

Flat 20% Off

Early Bird Discount

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Easy Installments

Detail
WEEKDAY - Filling Fast

calendar-icon122 Nov


6 weeks

USD 1199

USD 1019

Flat 15% Off

Enroll Now
WEEKDAY

calendar-icon106 Dec


6 weeks

USD 1199

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Not Sure Which Hadoop Training New York City Class to Join?  

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Big Data Hadoop Course Roadmap

Take a look at the benchmarks you will achieve during your Big Data Learning Path

Hadoop Architecture, HDFS and MapReduce

    • Introduction to BIGDATA and HADOOP.
    • Relation between Big Data and Hadoop.
    • What is the need of going ahead with Hadoop?
    • Scenarios to apt Hadoop Technology in REAL TIME Projects.
    • How Hadoop is addressing Big Data Changes
    • Importance of Hadoop Ecosystem Components
    • What is HDFS (Hadoop Distributed File System).
    • HDFS Architecture - 5 Daemons of Hadoop
    • Replication in Hadoop - Fail Over Mechanism
    • Hadoop Cluster Setup and JDK Installation.
    • Why is Map Reduce is essential in Hadoop?
    • MapReduce and drawbacks w.r.to Task Tracker Failure in Hadoop Cluster.
    • Map Reduce Life Cycle & Communication Mechanism of Job Tracker & Task Tracker

Unix Shell & Apache Pig Installation & HIVE Installation & User Defined Functions

    • Unix Shell & Apache Pig Installation
      • How to write a basic Map Reduce Program
      • Compression Techniques in Map Reduce
      • Unix Shell Scripting Basics and commands.
      • How Unix shell used in hadoop
      • PIG Installation (Hands on Installation on Laptops)
      • Introduction to Apache Pig
      • Map Reduce Vs Apache Pig
      • Where to Use Map Reduce and PIG in REAL Time Hadoop Projects
      • How to write a simple pig script
      • Parameter substitution in PIG Scripts
      • How to develop the Complex Pig Script
      • Bags , Tuples and fields in PIG
    • HIVE Installation & User Defined Functions
      • HIVE Installation(Hands on Installation on Laptops)
      • Local Mode & Clustered Mode
      • Hive Introduction and need of Apache HIVE in Hadoop
      • When to choose PIG & HIVE in REAL Time Project
      • Importance Of Hive Meta Store.
      • Communication mechanism with Metastore.
      • Hive Integration with Hadoop & Hive Query Language(Hive QL)
      • SQL VS Hive QL, Data Slicing Mechanisms and Partitions In Hive
      • Partitioning Vs Bucketing
      • Collection Data Types in HIVE
      • User Defined Functions(UDFs) in HIVE
      • UDFs, UDAFs, UDTFs and need of UDFs in HIVE
      • Hive Serializer/Deserializer - SerDe
      • Semi Structured Data Processing Using Hive(XML/JSON)
      • HIVE - HBASE Integration

SQOOP & Hbase Installation & YARN Architecture, Impala & Apache Spark With Scala

    • SQOOP & Hbase Installation
      • Sqoop installation with MySQL Client
      • Introduction to Sqoop.
      • MySQL client and Server Installation
      • How to connect to Relational Database using Sqoop
      • Different Sqoop Commands
      • Hive-Imports, Incremental import,
      • import all table and import using password on file
      • Hbase introduction and HDFS Vs Hbase
      • Hbase Data modeling Elements
      • Hbase Architecture & Clients(REST,Thrift,Java Based,Avro)
      • MongoDB basics & Introduction to MongoDB
      • Features of MongoDB
      • REAL Time Use Cases on Hadoop & MongoDB Use Cases
    • YARN Architecture, Impala & Apache Spark With Scala
      • What is YARN?
      • Difference between Map Reduce & YARN
      • YARN Architecture(Resource Manager,Application Master,Node Manager),
      • When should we go ahead with YARN
      • YARN Process flow and Web UI
      • Different Configuration Files for YARN.
      • What is Impala? & How can we use Impala for Query Processing?
      • When should we go ahead with Impala
      • HIVE Vs Impala
      • Real time Use Cases with Impala.
      • Interactive Scala - Scala Shell
      • Functional Programing in Scala
      • What is Functional Programming
      • Difference between Object Oriented and Functional
      • Flume Master , Flume Collector and Flume Agent
      • Real Time Use Case using Apache Flume.

Apache OOZIE and Spark

    • Oozie Introduction, Oozie Architecture & Job Submission
    • Spark Vs Map Reduce Processing
    • File Operations in Spark Shell.
    • Introduction to Spark Components.
    • What is RDD and why it is important in Spark
    • Core Features of RDD & Lazily Evaluated
    • Different Operation on RDDs
    • Actions and Transformation in RDD
    • Running Spark in a Clustered Mode.
    • Introduction to Spark SQL
    • The SQL Context, Hive Vs Spark SQL
    • Introduction to Data Frames [ Dfs ]

Introduction to Big Data and Hadoop

  • Hadoop career roadmap

    With the help of our Big Data Courses and the curriculum associated with it, many of our students have landed great jobs with high paying salary packages. Here is what we cover during the Hadoop Course.

    Here is what all we cover in our online Salesforce Course. Each topic has been detailed with the sub-topic that we cover.

Course Curriculum

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  • Introduce yourself to the concepts, principles and working knowledge of Hadoop
  • Understand the real world scenarios with real-time job oriented projects and case studies
  • Learn from World Class Trainers who are one amongst the top rated working IT Professionals
  • Clear your certifications while we make you ready for the huge job market present out there

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