Hadoop Training in New York, NYC

  • Get Trained for Microsoft Big Data Certification - Learn More
  • Become a Hadoop Developer by getting project experience
  • Build a project portfolio to connect with recruiters
    - Check out Toly's Portfolio
  • Get hands-on experience with access to remote Hadoop cluster
  • Stay updated in your career with lifetime access to live classes

Upcoming Live Hadoop Training in New York


19
Aug
Sat and Sun(4 weeks)
7:00 AM - 11:00 AM PST
$399

02
Sep
Sat and Sun(4 weeks)
7:00 AM - 11:00 AM PST
$399

Want to work 1 on 1 with a mentor. Choose the project track

About Online Hadoop Training Course

Project Portfolio

Build an online project portfolio with your project code and video explaining your project. This is shared with recruiters.

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42 hrs live hands-on sessions with industry expert

The live interactive sessions will be delivered through online webinars. All sessions are recorded. All instructors are full-time industry Architects with 14+ years of experience.

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Remote Lab and Projects

You will get access to a remote Hadoop cluster for this purpose. Assignments include running MapReduce jobs/Pig & Hive queries. The final project will give you a complete understanding of the Hadoop Ecosystem.

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Lifetime Access & 24x7 Support

Once you enroll for a batch, you are welcome to participate in any future batches free. If you have any doubts, our support team will assist you in clearing your technical doubts.

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Weekly 1-on-1 meetings

If you opt for the Microsoft Track, you will get 8 one-on-one meetings with an experienced Hadoop architect who will act as your mentor.

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Money Back Guarantee

DeZyre has a 'No Questions asked' 100% money back guarantee. You can attend the first 2 webinars and if you are not satisfied, please let us know before the 3rd webinar and we will refund your fees.

Big Data Hadoop Training in New York, NYC

The growth of open source technologies and prioritizing data quality over quantity is making a huge and lasting impact on the big data job market in New York. To remain competitive into the future data experts need to develop versatile skills in various big data technologies like Hadoop , Spark , Scala, Kafka, Python, R programming and other related big data technologies. There is a sky rocketing demand for big data professionals driven by the increasing number of consumer interactions across social media, cloud and mobile platforms.

Hadoop Developer Salary in New York, NYC

  • Average Big Data Hadoop Developer Salary in New York, NY is $140,000.
  • Average Java Hadoop Developer Salary in New York, NY is $154,000.

Companies Hiring Hadoop Developers in NYC

 
  • Bloomberg
  • Citi
  • Datadog
  • Google
  • JP Morgan
  • KPMG
  • NASDAQ
  • NBCUniversal
  • Smith & Keller
  • TEK Systems
  • Viacom

Hadoop Certification Cost in New York, NY- $399

DeZyre's Hadoop Developer Certification Training in New York costs around $399 featuring instructor-led online hadoop training and industry oriented hadoop projects. DeZyre provides hadoop certification to professionals on successful completion and evaluation of the hadoop project by industry experts.

Benefits of Hadoop Training online

How will this help me get jobs?

  • Display Project Experience in your interviews

    The most important interview question you will get asked is "What experience do you have?". Through the DeZyre live classes, you will build projects, that have been carefully designed in partnership with companies.

  • Connect with recruiters

    The same companies that contribute projects to DeZyre also recruit from us. You will build an online project portfolio, containing your code and video explaining your project. Our corporate partners will connect with you if your project and background suit them.

  • Stay updated in your Career

    Every few weeks there is a new technology release in Big Data. We organise weekly hackathons through which you can learn these new technologies by building projects. These projects get added to your portfolio and make you more desirable to companies.

What if I have any doubts?

For any doubt clearance, you can use:

  • Discussion Forum - Assistant faculty will respond within 24 hours
  • Phone call - Schedule a 30 minute phone call to clear your doubts
  • Skype - Schedule a face to face skype session to go over your doubts

Do you provide placements?

In the last module, DeZyre faculty will assist you with:

  • Resume writing tip to showcase skills you have learnt in the course.
  • Mock interview practice and frequently asked interview questions.
  • Career guidance regarding hiring companies and open positions.

Online Hadoop Training Course Curriculum

Module 1

Introduction to Big Data

  • Rise of Big Data
  • Compare Hadoop vs traditonal systems
  • Hadoop Master-Slave Architecture
  • Understanding HDFS Architecture
  • NameNode, DataNode, Secondary Node
  • Learn about JobTracker, TaskTracker
Module 2

HDFS and MapReduce Architecture

  • Core components of Hadoop
  • Understanding Hadoop Master-Slave Architecture
  • Learn about NameNode, DataNode, Secondary Node
  • Understanding HDFS Architecture
  • Anatomy of Read and Write data on HDFS
  • MapReduce Architecture Flow
  • JobTracker and TaskTracker
Module 3

Hadoop Configuration

  • Hadoop Modes
  • Hadoop Terminal Commands
  • Cluster Configuration
  • Web Ports
  • Hadoop Configuration Files
  • Reporting, Recovery
  • MapReduce in Action
Module 4

Understanding Hadoop MapReduce Framework

  • Overview of the MapReduce Framework
  • Use cases of MapReduce
  • MapReduce Architecture
  • Anatomy of MapReduce Program
  • Mapper/Reducer Class, Driver code
  • Understand Combiner and Partitioner
Module 5

Advance MapReduce - Part 1

  • Write your own Partitioner
  • Writing Map and Reduce in Python
  • Map side/Reduce side Join
  • Distributed Join
  • Distributed Cache
  • Counters
  • Joining Multiple datasets in MapReduce
Module 6

Advance MapReduce - Part 2

  • MapReduce internals
  • Understanding Input Format
  • Custom Input Format
  • Using Writable and Comparable
  • Understanding Output Format
  • Sequence Files
  • JUnit and MRUnit Testing Frameworks
Module 7

Apache Pig

  • PIG vs MapReduce
  • PIG Architecture & Data types
  • PIG Latin Relational Operators
  • PIG Latin Join and CoGroup
  • PIG Latin Group and Union
  • Describe, Explain, Illustrate
  • PIG Latin: File Loaders & UDF
Module 8

Apache Hive and HiveQL

  • What is Hive
  • Hive DDL - Create/Show Database
  • Hive DDL - Create/Show/Drop Tables
  • Hive DML - Load Files & Insert Data
  • Hive SQL - Select, Filter, Join, Group By
  • Hive Architecture & Components
  • Difference between Hive and RDBMS
Module 9

Advance HiveQL

  • Multi-Table Inserts
  • Joins
  • Grouping Sets, Cubes, Rollups
  • Custom Map and Reduce scripts
  • Hive SerDe
  • Hive UDF
  • Hive UDAF
Module 10

Apache Flume, Sqoop, Oozie

  • Sqoop - How Sqoop works
  • Sqoop Architecture
  • Flume - How it works
  • Flume Complex Flow - Multiplexing
  • Oozie - Simple/Complex Flow
  • Oozie Service/ Scheduler
  • Use Cases - Time and Data triggers
Module 11

NoSQL Databases

  • CAP theorem
  • RDBMS vs NoSQL
  • Key Value stores: Memcached, Riak
  • Key Value stores: Redis, Dynamo DB
  • Column Family: Cassandra, HBase
  • Graph Store: Neo4J
  • Document Store: MongoDB, CouchDB
Module 12

Apache HBase

  • When/Why to use HBase
  • HBase Architecture/Storage
  • HBase Data Model
  • HBase Families/ Column Families
  • HBase Master
  • HBase vs RDBMS
  • Access HBase Data
Module 13

Apache Zookeeper

  • What is Zookeeper
  • Zookeeper Data Model
  • ZNokde Types
  • Sequential ZNodes
  • Installing and Configuring
  • Running Zookeeper
  • Zookeeper use cases
Module 14

Hadoop 2.0, YARN, MRv2

  • Hadoop 1.0 Limitations
  • MapReduce Limitations
  • HDFS 2: Architecture
  • HDFS 2: High availability
  • HDFS 2: Federation
  • YARN Architecture
  • Classic vs YARN
  • YARN multitenancy
  • YARN Capacity Scheduler
Module 15

Project

  • Demo of 2 Sample projects.
  • Twitter Project : Which Twitter users get the most retweets? Who is influential in our industry? Using Flume & Hive analyze Twitter data.
  • Sports Statistics : Given a dataset of runs scored by players using Flume and PIG, process this data find runs scored and balls played by each player.
  • NYSE Project : Calculate total volume of each stock using Sqoop and MapReduce.
Module 1

Learn Hadoop on HDInsight (Linux)

  • What is Hadoop on HDInsight?
  • How is data stored in HDInsight?
  • Information about using HDInsight on Linux
  • Using SSH with Linux clusters from a Linux computer
  • SSH Tunneling to HDInsight Linux clusters
Module 2

Processing Big Data with Hadoop in Azure HDInsight

  • Provision an HDInsight cluster.
  • Connect to an HDInsight cluster, upload data, and run MapReduce jobs.
  • Use Hive to store and process data.
  • Process data using Pig.
  • Use custom Python user-defined functions from Hive and Pig.
  • Define and run workflows for data processing using Oozie.
  • Transfer data between HDInsight and databases using Sqoop.
Module 3

Implementing Real-Time Analytics with Hadoop in Azure HDInsight

  • Use HBase to implement low-latency NoSQL data stores.
  • Use Storm to implement real-time streaming analytics solutions.
  • Use Spark for high-performance interactive data analysis.
Module 4

Implementing Predictive Analytics with Spark in Azure HDInsight

  • Using Spark to explore data and prepare for modeling
  • Build supervised machine learning models
  • Evaluate and optimize models
  • Build recommenders and unsupervised machine learning models
Module 5

Project

  • Implement a Big Data Project under the guidance of a Hadoop Architect
  • Upload your project to DeZyre portfolio and display to recruiters

Upcoming Classes for Online Hadoop Training in New York, NYC

August 19th

  • Duration: 4 weeks
  • Days: Sat and Sun
  • Time: 7:00 AM - 11:00 AM PST
  • 8 thirty minute 1-to-1 meetings with an industry mentor
  • Customized doubt clearing session
  • 1 session per week
  • Total Fees $399
    Pay as little as $66/month for 6 months, during checkout with PayPal
  • Enroll

September 2nd

  • Duration: 4 weeks
  • Days: Sat and Sun
  • Time: 7:00 AM - 11:00 AM PST
  • 8 thirty minute 1-to-1 meetings with an industry mentor
  • Customized doubt clearing session
  • 1 session per week
  • Total Fees $399
    Pay as little as $66/month for 6 months, during checkout with PayPal
  • Enroll
 

Online Hadoop Training Course Reviews

See all 317 Reviews

Hadoop Developers in New York, NYC

  • Montu P

    Former Hadoop Data Engineer - Looking for a New Full Time Opportunity

    Inovalon (Employer - Unicon Labs http://unicon-labs.com/)

  • Sakti Mishra

    Hadoop Lead

    Cognizant, Dun & Bradstreet

  • Raghu Tirunahari

    Big data developer

    American Express

Big Data and Hadoop Blogs

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Hadoop Cluster Overview: What it is and how to setup one?


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Recap of Apache Spark News for August


News on Apache Spark - August 2016 ...

DeZyre Reviews: Online Hadoop Training Class of July 25 2015


The Hadoop online training session at DeZyre is conducted through 42 hours of live webinar session where an industry expert explains all the ...

Online Hadoop Training MeetUp

Jupyter, Graph and More....

Description: Please join us for a "Jupyter, Graph, and More" Meetup in NYC - Presenters include : - Jason Plurad - JanusGraph: What's Next, Project Status Update - Ray Canzanese - Alert prioritization in a security event graph - Susan Malaika - Extensions for Graph in SQL - Luke Schantz - Harness the power of cognitive data analysis in a Jupyter Notebook with PixieDust - Luciano Resende - Building an Anal ...

Hosted By: Big Data Developers in NYC
Event Time: 2017-08-23 03:30:00

Online Hadoop Training News

All your streaming data are belong to Kafka

Description:

Apache Kafka is on a roll. Last year it registered a 260 percent jump in developer popularity, as Redmonk’s Fintan Ryan highlights, a number that has only ballooned since then as IoT and other enterprise demands for real-time, streaming data become common. Hatched at LinkedIn, Kafka’s founding engineering team spun out to form Confluent, which has been a primary developer of the Apache project ever since.

But not the only one. Indeed, given the rising importance of Kafka, more companies than ever are committing code, including Eventador, started by Kenny Gorman and Erik Beebe, both co-founders of ObjectRocket (acquired by Rackspace). Whereas ObjectRocket provides the MongoDB database as a service, Eventador offers a fully managed Kafka service, further lowering the barriers to streaming data.

To read this article in full or to leave a comment, please click here

Date Posted: Mon, 31 Jul 2017 03:00:00 -0700

12 'hot' technologies not living up to the hype

Description:

This is tech. We make the future. However, we often get a little ahead of ourselves. Oftentimes the promise isn’t fulfilled as soon or as well as we imagined or vapored forth. Here is my list of stuff that may be good, but perhaps isn’t all that it’s cracked up to be as of mid-2017.

1. Chatbots

It is ironic that I’d call chatbots a bit overhyped given that I work for a search company (full disclosure: I work for Lucidworks, a search technology firm with products in this area). I don’t mean to say that NLP and conversational search and such don’t have a very bright future, but chatbots will only be useful as an interface to a search engine—as the thing that asks follow-up questions to refine your search to find exactly what you’re looking for. All of the other uses, like the one that tries to sell you something or tries to work in customer service, are just fancy dressed up IVR systems.

To read this article in full or to leave a comment, please click here

Date Posted: Thu, 06 Jul 2017 03:00:00 -0700

IDG Contributor Network: The siren song of Hadoop

Description:

Hadoop seems incredibly well-suited to shouldering machine-learning workloads. With HDFS you can store both structured and unstructured data across a cluster of machines, and SQL-on-Hadoop technologies like Hive make those structured data look like database tables. Execution frameworks like Spark let you distribute compute across the cluster as well. On paper, Hadoop is the perfect environment for running compute-intensive distributed machine learning algorithms across a vast amount of data.

Unfortunately, though, Hadoop seems incredibly well-suited for a lot of other things too. Streaming data? Storm and Flink! Security? Kerberos, Sentry, Ranger, and Knox! Data movement and message queues? Flume, Sqoop, and Kafka! SQL? Hive, Impala and Hawq! The Hadoop ecosystem has become a bag of often overlapping and competing technologies. Cloudera vs. Hortonworks vs. MapR is responsible for some of this, as is the dynamism of the open source community.

To read this article in full or to leave a comment, please click here

Date Posted: Tue, 23 May 2017 09:30:00 -0700

Hadoop Tutorials

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