Hadoop Training and Certification in Pune | Sulekha

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    Hadoop Training in Pune as on Feb 24, 2018

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

      703 Reviews 8.8 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. Paratus Systems Pvt. Ltd., Aundh

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

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

    3. Technogeeks, Aundh

      8 Reviews 7.5 Sulekha Score
      +91 73045 21859
      Hadoop Training, Informatica training

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

    4. QSpiders, J.M. Road

      36 Reviews 6.7 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. +91 90 21116331
      Hadoop Training, Big data & Hadoop training

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

    6. Radical Technologies, Aundh

      2321 Reviews 10.0 Sulekha Score
      +91 90211 08995
      Hadoop Training, SAS training

      #2nd Floor, Trade Field Building, Office No. 9, Sanghvi Nagar, Aundh, Pune - 411007 Get Directions

    7. +91 90 21113919
      Hadoop Training, Big data & Hadoop training

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

    8. Advanto Software Pvt. Ltd., Karve Nagar

      26 Reviews 7.2 Sulekha Score
      +91 95790 58355
      Hadoop Training, Big data & Hadoop training

      2nd Floor, Gurukul Bungalow, Karve Nagar, Pune - 411052 Get Directions

    9. Seven Mentor Pvt. Ltd., Shivaji Nagar

      240 Reviews 8.3 Sulekha Score
      +91 90211 12015
      Hadoop Training, Big data & Hadoop training

      A-25, 1184/4, Shreenath Plaza, 1st Floor, Dnyaneshwar Paduka Chowk, Shivaji Nagar, Pune - 411006

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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