What Is Hadoop? | Introduction To Hadoop | Hadoop Tutorial For Beginners | Simplilearn

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    🔥 Enroll for FREE Big Data Hadoop Spark Course & Get your Completion Certificate: https://www.simplilearn.com/learn-hadoop-spark-basics-skillup?utm_campaign=Hadoop&utm_medium=DescriptionFirstFold&utm_source=youtube
    This Hadoop tutorial will help you understand what is Big Data, what is Hadoop, how Hadoop came into existence, what are the various components of Hadoop and an explanation on Hadoop use case. Below topics are explained in this Hadoop tutorial:

    Below topics are explained in this Hadoop tutorial:
    (02:30)The rise of Big Data
    (06:31)What is Big Data?
    (09:40)Big Data and its challenges
    (11:17)Hadoop as a solution
    (11:31)What is Hadoop?
    (11:51)Components of Hadoop
    (25:16)Use case of Hadoop

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    To access the slides, click here: https://www.slideshare.net/Simplilearn/what-is-hadoop-what-is-big-data-hadoop-introduction-to-hadoop-hadoop-tutorial-simplilearn/Simplilearn/what-is-hadoop-what-is-big-data-hadoop-introduction-to-hadoop-hadoop-tutorial-simplilearn

    Watch more videos on HadoopTraining: https://www.youtube.com/watch?v=CKLzDWMsQGM&list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ

    #Hadoop #WhatIsHadoop #BigData #Hadooptutorial #HadoopTutorialForBeginners #LearnHadoop #HadoopTraining #HadoopCertification #SimplilearnHadoop #Simplilearn

    Simplilearn’s Big Data Hadoop training course lets you master the concepts of the Hadoop framework and prepares you for Cloudera’s CCA175 Big data certification. With our online Hadoop training, you’ll learn how the components of the Hadoop ecosystem, such as Hadoop 3.4, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark, etc. fit in with the Big Data processing lifecycle. Implement real life projects in banking, telecommunication, social media, insurance, and e-commerce on CloudLab.

    What is this Big Data Hadoop training course about?
    The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.

    What are the course objectives?
    This course will enable you to:
    1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
    2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
    3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
    4. Get an overview of Sqoop and Flume and describe how to ingest data using them
    5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
    6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
    7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
    8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
    9. Gain a working knowledge of Pig and its components
    10. Do functional programming in Spark

    Who should take up this Big Data and Hadoop Certification Training Course?
    Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals:
    1. Software Developers and Architects
    2. Analytics Professionals
    3. Senior IT professionals
    4. Testing and Mainframe professionals
    5. Data Management Professionals
    6. Business Intelligence Professionals
    7. Project Managers
    8. Aspiring Data Scientists

    Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=What-is-Hadoop-iANBytZ26MI&utm_medium=Tutorials&utm_source=youtube

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    25 COMMENTS

    1. I love the teaching and useful knowledge you provide for us. Although my ears hurt either cuz the mic is too close to the mouth or something else, so I can’t even finish watching these amazing videos, unfortunately