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    Hadoop Training in Pune as on Apr 26, 2018

    1. 3RI Technologies Pvt. Ltd., Pimple Saudagar

      710 Reviews 7.2 Sulekha Score
      +91 76206 44895
      Hadoop Training, Business intelligence & analytics training

      Rainbow Plaza ,Office No. 403/405, 4th Floor, Pimple Saudagar, Pune - 411027 Get Directions

    2. Technogeeks, Aundh

      13 Reviews 6.3 Sulekha Score
      +91 73045 21859
      Hadoop Training, Informatica training

      Plot No. 34B, 1st Floor, Tejaswini Society, Aundh, Pune - 411007 Get Directions

    3. Paratus Systems Pvt. Ltd., Aundh

      62 Reviews 6.5 Sulekha Score
      +91 73048 42690
      Hadoop Training, Big data & Hadoop training

      A1, Krishnamayee Apartment, ITI Road, Aundh, Pune - 411007 Get Directions

    4. QSpiders, J.M. Road

      46 Reviews 5.9 Sulekha Score
      +91 90211 04234
      Hadoop Training, Big data & Hadoop training

      Puttannachetty Complex ,No. 582, Sunny Pride, 5th Floor, J.M. Road, Pune - 411004

    5. Ethans Technologies, Pimple Saudagar

      100 Reviews 6.1 Sulekha Score
      +91 90211 12130
      Hadoop Training, Business intelligence & analytics training

      Fortuna Building ,Solitaire residency gate,1st floor, above Honda showroom, Rahatni road, Pimple Saudagar, Pune - 411027 Get Directions

    6. +91 90 21116331
      Hadoop Training, Big data & Hadoop training

      JM Road, Sahil Arcade, 1st Floor, Deccan Gymkhana, Pune - 411004

    7. ETL HIVE, Pimple Saudagar

      47 Reviews 5.0 Sulekha Score
      +91 90211 08198
      Hadoop Training, Informatica training

      ETLhive, Floor #03, Shreeji Vihar, Kunal Icon Road, Pimple Saudagar, Pune - 411027 Get Directions

    8. +91 90211 10442
      Hadoop Training, Big data & Hadoop training

      Preet Archade, 1st Floor, Dhankawadi, Pune - 411043 Get Directions

    9. Orilent Technologies Pvt.Ltd, Hadapsar

      1 Review 4.7 Sulekha Score
      +91 90 21113919
      Hadoop Training, Big data & Hadoop training

      Office No.7&8, 2nd Floor,Manisha Blitz, Hadapsar, Pune - 411013

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    3 Reviews of Hadoop Training in Pune as on Apr 26, 2018

    Average Rating (4) - 3 reviews
    1. 18th August, 2017

      Interested in Big Data Training, so I have joined in SEED Infotech Pvt. Ltd., the course duration is about 2.5 months and the fees amount was 20000..the faculty was really good, they were always available to clear all doubt of the students, it gains knowledge to me.I hope it will help to upgrade my career...very happy to join in the Institute.

      1
    2. 18th July, 2017

      Have enrolled in this center for Big data and Hadoop coaching. The coaching was worthy and useful and the faculty is friendly and outstanding and the duration is 3 months with class taken on the weekends. The fee is 7000 and happy to join here.

      5
    3. 13th July, 2017

      Excellent service on time. Exact match found.

      1
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    • Hadoop Training – Commonly Asked Questions

      Hadoop is an open source project created by Apache which is primarily used for processing and storage of large data in a distributed environment. Hadoop has become extremely popular because it can scale up from a single server to multiple ones. This framework is used across the world by various big players such as Amazon, Facebook, and IBM etc. The need for Hadoop specialists and data scientists has increased by leaps lately leading to more lucrative opportunities for specialists.

      • What is the duration of this course?

        The duration of this course are as follows:

        • Regular Classes: 1 month (Monday to Friday)
        • Weekend Classes: 8 weeks (Saturday, Sunday and Holidays)
        • Fast Track Classes: 15 days (Daily classes)
      • What are the pre-requisites for this course?

        There are no specific pre-requisites to learn Hadoop. However, knowledge in the following things can be an added advantage:

        • Basic understanding of JAVA and Linux
        • Basic knowledge of nodes and clusters
        • Broad understanding of Database and SQL
        • Basic knowledge in programming languages such as Java and python
        • A basic understanding of the Hadoop architecture
      • What are the learning objectives of this course?

        The learning objectives of this course are as follows:

        • In-depth understanding of the Hadoop working environment
        • Understanding the integration of SQL databases to Hadoop
        • In depth understanding of various components such as HDFS, Flume, Sqoop and PIG
        • An overview of machine learning and how it works

      Course contents

      Introduction to Big Data

      • Overview of Big Data
      • Introduction
      • Characteristics of Big Data
      • Cleanup
      • Big Data collection
      • Analyzing with Big Data
      • Importance of parallel computing
      • Product types used for handling big data

      Introduction to Hadoop

      • Hadoop stack
      • The various components used in Hadoop
      • Process types used in Hadoop
      • Understanding Hadoop environment
      • Why is Hadoop used
      • Data analytics importance
      • Setting up Hadoop environment
      • Hadoop vs RDMS

      HDFS (Hadoop file system)

      • File system types
      • Explaining these file systems
      • Basic file commands used
      • Web based UI
      • High availability
      • Clustering methodology
      • Master nodes
      • Slave nodes
      • View status on Hadoop prompt
      • Viewing status on Web UI
      • Hadoop commands
      • Using web console
      • Creating and accessing lib

      YARN

      • Overview of YARN
      • YARN architecture
      • Using scheduler and resource manager

      Installation and configuration of Hadoop

      • Installation types
      • Hadoop distributions used
      • Directory structure of Hadoop
      • Hadoop installation for Linux
      • XML
      • Master and slave files
      • Checking the system and file system health
      • Benchmarking cluster

      Mapreduce

      • Introduction to MapReduce
      • Mapreduce programming
      • Word count
      • Mapreduce nodes
      • Task tracker
      • Web console and map reduce

      Advanced administration

      • Authorization
      • Superuser
      • Secure mode
      • Failover
      • Managing quotas
      • Enabling thrash

      Hadoop JAQL

      • Introduction to JAQL
      • Information stream and ocean
      • Using JAQL language

      Hive

      • Overview of data warehousing
      • Requirement of data warehousing
      • Hive and data warehousing
      • Hive environment
      • Hive query language
      • DDL approach through hive
      • DML approach using hive

      Hadoop Pig

      • Overview of PIG
      • Using PIG script
      • Streaming data analytics with PIG
      • Pros and Cons of using PIG
      • Managing PIG script
      • PIG stream requirement

      FLUME and SQOOP

      • FLUME and SQOOP methodology
      • Advantages of FLUME
      • Requirement for FLUME and SQOOP
      • Advantages of SQOOP

      Big R and Ozie

      • Introduction to Big R and Ozie
      • Advantages
      • Working lifecycle of Ozie
      • Ozie data flow
      • Setting up ozie
      • Ozie scheduling

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