OverviewTraining OptionsCourse CurriculumExam & CertificationReviewsFAQs

Course Overview

Training Options

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  • Blended learning delivery model (self-paced eLearning and/or instructor-led options)
  • Flexible pricing options
  • Enterprise grade Learning Management System (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Course Curriculum

Course Content

  • Introduction to Big Data and Hadoop

    Preview

    • Lesson 1.0 - Introduction to Big Data and Hadoop

      29:37Preview
      • 1 Introduction to Big Data and Hadoop
        00:21
      • 2 Objectives
        00:26
      • 3 Need for Big Data
        01:42
      • 4 Three Characteristics of Big Data
        00:35
      • 5 Characteristics of Big Data Technology
        01:52
      • 6 Appeal of Big Data Technology
        00:50
      • 7 Handling Limitations of Big Data
        00:49
      • 8 Introduction to Hadoop
        01:00
      • 9 Hadoop Configuration
        00:53
      • 10 Apache Hadoop Core Components
        00:36
      • 11 Hadoop Core Components—HDFS
        01:07
      • 12 Hadoop Core Components—MapReduce
        00:45
      • 13 HDFS Architecture
        01:13
      • 14 Ubuntu Server—Introduction
        00:51
      • 15 Hadoop Installation—Prerequisites
        00:26
      • 16 Hadoop Multi-Node Installation—Prerequisites
        00:29
      • 17 Single-Node Cluster vs. Multi-Node Cluster
        00:49
      • 18 MapReduce
        01:09
      • 19 Characteristics of MapReduce
        00:56
      • 20 Real-Time Uses of MapReduce
        01:01
      • 21 Prerequisites for Hadoop Installation in Ubuntu Desktop 12.04
        00:20
      • 22 Hadoop MapReduce—Features
        00:52
      • 23 Hadoop MapReduce—Processes
        00:48
      • 24 Advanced HDFS–Introduction
        00:47
      • 25 Advanced MapReduce
        00:55
      • 26 Data Types in Hadoop
        01:15
      • 27 Distributed Cache
        00:41
      • 28 Distributed Cache (contd.)
        00:40
      • 29 Joins in MapReduce
        00:44
      • 30 Introduction to Pig
        00:40
      • 31 Components of Pig
        01:00
      • 32 Data Model
        00:43
      • 33 Pig vs. SQL
        01:07
      • 34 Prerequisites to Set the Environment for Pig Latin
        00:20
      • 35 Summary
        00:55

    • Lesson 1.1 - Hive HBase and Hadoop Ecosystem Components

      29:59Preview
      • 1 Hive, HBase and Hadoop Ecosystem Components
        00:22
      • 2 Objectives
        00:23
      • 3 Hive—Introduction
        00:55
      • 4 Hive—Characteristics
        01:20
      • 5 System Architecture and Components of Hive
        00:18
      • 6 Basics of Hive Query Language
        00:38
      • 7 Data Model—Tables
        00:32
      • 8 Data Types in Hive
        00:16
      • 9 Serialization and De serialization
        01:19
      • 10 UDF/UDAF vs. MapReduce Scripts
        00:47
      • 11 HBase—Introduction
        01:15
      • 12 Characteristics of HBase
        00:42
      • 13 HBase Architecture
        01:04
      • 14 HBase vs. RDBMS
        01:08
      • 15 Cloudera—Introduction
        00:44
      • 16 Cloudera Distribution
        01:07
      • 17 Cloudera Manager
        00:34
      • 18 Hortonworks Data Platform
        00:42
      • 19 MapR Data Platform
        00:43
      • 20 Pivotal HD
        00:53
      • 21 Introduction to ZooKeeper
        00:23
      • 22 Features of ZooKeeper
        01:12
      • 23 Goals of ZooKeeper
        00:38
      • 24 Uses of ZooKeeper
        00:49
      • 25 Sqoop—Reasons to Use It
        01:26
      • 26 Sqoop—Reasons to Use It (contd.)
        01:09
      • 27 Benefits of Sqoop
        00:42
      • 28 Apache Hadoop Ecosystem
        00:59
      • 29 Apache Oozie
        00:43
      • 30 Introduction to Mahout
        00:22
      • 31 Usage of Mahout
        00:28
      • 32 Apache Cassandra
        00:54
      • 33 Apache Spark
        01:28
      • 34 Apache Ambari
        00:32
      • 35 Key Features of Apache Ambari
        00:51
      • 36 Hadoop Security—Kerberos
        00:53
      • 37 Summary
        00:48

    • Lesson 1.2 - Quiz

      • Quiz

    • Lesson 1.3 - Thank You

      00:09Preview
      • Thank You
        00:09

Contact Us

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Exam & Certification

  • What qualifications do you need?

    There are no prerequisites for this course.

  • What do I need to do to unlock my Simplilearn certificate?

    • Complete 85% of the course.
    • Complete 1 simulation test with a minimum score of 60%.

Reviews

  • Cadence Serna

    Cadence Serna

    Customer Lifecycle Management at AT&T

    For an introduction, this is still very dense. There's a lot to take in; it's a very broad and detailed top-down look at big data. I'm very glad to have taken the time to view this intro.

  • Sachindra Kumar

    Sachindra Kumar

    Simplilearn has given me the right exposure to new courses and extremely handy knowledge. Now I can enhance based on my practice. The best experience for me is the project which requires action based on what you learn from the course.

  • Shubham Das

    Shubham Das

    SCM Analyst at Tata Consultancy Services

    The course is very informative and detailed.

  • Venkat Nagender

    Venkat Nagender

    Solution Architect @ Ericsson

    Very nice and easily understandable. All important topics are covered.

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Why Join this Program

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts

FAQs

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Related Programs

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  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, OPM3 and the PMI ATP seal are the registered marks of the Project Management Institute, Inc.