Hadoop Training and Certification in Hyderabad | Sulekha

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    Hadoop Training in Hyderabad as on Feb 23, 2018

    1. Blue Nest Training Services, Ameerpet

      3 Reviews 4.8 Sulekha Score
      +91 75690 02179
      Hadoop Training, Big data & Hadoop training

      Manjeera Square ,Manjeera Square, Ground Floor, Ameerpet, Hyderabad - 500016

    2. +91 75690 03753
      Hadoop Training, Business intelligence & analytics training

      Croma Store Building ,4th Floor, Nagarjuna Ikon, Kondapur X Road, Kondapur, Hyderabad - 500084

    3. +91 75690 02209
      Hadoop Training, Big data & Hadoop training

      1st Floor, Madhura Nagar Colony, Khajaguda, Rai Durg, Gachibowli, Hyderabad - 500032 Get Directions

    4. R & D Trainings, Ameerpet

      1 Review 5.9 Sulekha Score
      +91 75690 02308
      Hadoop Training, Big data & Hadoop training

      Ramakrishana Building ,2nd Cross, Ameerpet, Hyderabad - 500016 Get Directions

    5. RGS IT Solutions, Ameerpet

      60 Reviews 6.6 Sulekha Score
      +91 76708 24158
      Hadoop Training, Big data & Hadoop training

      Reliance Global House ,Plot No. 26, Durga Nagar Colony, Ameerpet, Hyderabad - 500016 Get Directions

    6. United Global Soft, Himayat Nagar

      35 Reviews 7.4 Sulekha Score
      +91 75 69018394
      Hadoop Training, SAS training

      No. 307, 5th Floor, Liberty Plaza, Himayat Nagar, Hyderabad - 500029

    7. AADS Education, Panjagutta

      46 Reviews 7.3 Sulekha Score
      +91 80999 39496
      Hadoop Training, Big data & Hadoop training

      Shreeya Enclave ,1st Floor, Panjagutta, Hyderabad - 500082 Get Directions

    8. +91 75690 06181
      Hadoop Training, SAS training

      Nandini Enclave, Flat No. 302, Addagutta Society, Pragathi Nagar Road,, JNTU Kukatpally, Hyderabad - 500072 Get Directions

    9. S.R. Technologies, Mehdipatnam

      1 Review 6.7 Sulekha Score
      +91 75 69018687
      Hadoop Training, Big data & Hadoop training

      No. 221, 1st Floor, Safa Arcade, Mehdipatnam, Hyderabad - 500028

    10. +91 75690 06783
      Hadoop Training, Big data & Hadoop training

      Plot No. 53/3RT, 1st Floor, Thobgha Terrain, S.R. Nagar, Hyderabad - 500038 Get Directions

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    Recent Enquiries on Data Science & Business Analytics Training

    • Technology: Hadoop
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    • Technology: Apache Hadoop
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    16 days ago
    • Hadoop Training: Course Pre-requisites, Objectives, Duration, and Syllabus

      Hadoop is a framework based on Java programming language, capable of managing and processing huge sets of data. In terms of its utility, Hadoop helps organisations make interpretations and draw insights from structured, semi-structured and unstructured data.

      Now, from one's career standpoint, you might well be thrilled to know that organisations are in need of Hadoop professionals who can help them manage data and make business decisions as well, by processing the gathered data. And, in this day and age when data sources are aplenty and consequently accumulation of data is also massive, the significance and current demand for Hadoop professionals just cannot be stressed enough.

      If working with data is of interest to you—few aspects are more interesting than managing and analysing data—then there is no reason why you should not consider enrolling yourself into Hadoop training course. Below are the ‘aspects to know’ before you enrol yourself into Hadoop training. Read on!

      Course Pre-requisites

      The fundamental pre-requisites for candidates who want to enrol into Hadoop certification course are:

      • Knowledge about Java will be a major fillip
      • Prior knowledge of Linux, the operating system on which Hadoop runs, will also be advantageous

      Course Objectives

      Hadoop training is aimed at:

      • Giving candidates a proper understanding of big data analytics and data processing
      • Teaching candidates to use Pig and Hive to run queries
      • Teaching them to load data into the HDFS file system

      Course Duration

      90-100 hours is the quintessential duration of Hadoop certification course, with instructor-led training, practical and self-learning completed during the above mentioned period. Training institutes afford their candidates tremendous flexibility in class timings, meaning you can balance your work schedule along with the Hadoop training schedule.

      Course Syllabus

      The Case for Apache Hadoop

      • Brief History of Hadoop
      • Core Hadoop Components
      • Fundamental Concepts

      Hadoop Distributed File System

      • HDFS Features
      • HDFS Design Assumptions
      • Overview of HDFS Architecture
      • Writing and Reading Files
      • Name Node Considerations
      • An Overview of HDFS Security
      • Hands-On Exercise


      • What Is MapReduce?
      • Features of MapReduce
      • Basic MapReduce Concepts
      • Architectural Overview
      • MapReduce Version 2
      • Failure Recovery
      • Hands-On Exercise

      Overview of the Hadoop Ecosystem

      • What is the Hadoop Ecosystem?
      • Integration Tools
      • Analysis Tools
      • Data Storage and Retrieval Tools

      Planning your Hadoop Cluster

      • General planning Considerations
      • Choosing the Right Hardware
      • Network Considerations
      • Configuring Nodes

      Hadoop Installation

      • Deployment Types
      • Installing Hadoop
      • Using Hadoop Manager for Easy Installation
      • Basic Configuration Parameters
      • Hands-On Exercise

      Advanced Configuration

      • Advanced Parameters
      • Configuring Rack Awareness
      • Configuring Federation
      • Configuring High Availability
      • Using Configuration Management Tools

      Hadoop Security

      • Why Is Hadoop Security Important?
      • Hadoop’s Security System Concepts
      • What Kerberos Is and How it Works?
      • Configuring Kerberos Security
      • Integrating a Secure Cluster with Other Systems

      Managing and Scheduling Jobs

      • Managing Running Jobs
      • Hands-On Exercise
      • FIFO Scheduler
      • Fair Scheduler
      • Configuring the Fair Scheduler
      • Hands-On Exercise

      Cluster Maintenance

      • Checking HDFS Status
      • Hands-On Exercise
      • Copying Data between Clusters
      • Adding and Removing Cluster Nodes
      • Rebalancing the Cluster
      • Hands-On Exercise
      • NameNode Metadata Backup
      • Cluster Upgrading

      Cluster Monitoring and Troubleshooting

      • General System Monitoring
      • Managing Hadoop’s Log Files
      • Using the NameNode and JobTracker Web UIs
      • Hands-On Exercise
      • Cluster Monitoring with Ganglia
      • Common Troubleshooting Issues
      • Benchmarking Your Cluster

      Populating HDFS from External Sources

      • An Overview of Flume
      • Hands-On Exercise
      • An Overview of Sqoop
      • Best Practices for Importing Data

      Installing and Managing Other Hadoop Projects

      • Apache Hive
      • Apache Pig
      • Apache HBase

      Hadoop Distributed File System (HDFS)

      • HDFS Design
      • HDFS Daemons
      • HDFS Federation
      • HDFS HA
      • Securing HDFS (Kerberos)
      • File Read and Write Paths

      Closing Thoughts

      Data accumulation and the need to manage huge sets of data are unlikely to diminish, simply because data sources are innumerable and they too are unlikely to come down in the years to come. Data scientists, data analysts, business analysts, and other personnel required to manage data, are in demand already and their stock is likely to go up in the coming years. Therefore, if you are looking for a change in career or are just starting out as a fresher, then big data analytics and Hadoop are areas you can consider entering into. This is a lucrative and one of the more interesting career options.