Course description

  • What is this course about?

    The ‘Introduction to Big Data and Hadoop’ is an ideal course package for individuals who want to understand the basic concepts of Big Data and Hadoop. On completing this course, learners will be able to interpret what goes behind the processing of huge volumes of data as the industry switches over from excel-based analytics to real-time analytics.

    The course focuses on the basics of Big Data and Hadoop. It further provides an overview of the commercial distributions of Hadoop as well as the components of the Hadoop ecosystem. 

  • Why the course is most sought after?

    Big Data Analytics is widely used to analyze large volumes of data. The growing need for professionals equipped with the knowledge of Big Data and Hadoop has increased opportunities for those who want to make a career in this field. Knowing the basics of Big Data and Hadoop will make it easier for such professionals to pursue advanced level courses in this subject and acquire skills to become experts in Big Data analytics.
     
    Knowledge of Big Data and Hadoop enables you to install and configure Hadoop components and manage as well as integrate large sets of unstructured data. The following examples show why you should get equipped with the knowledge of Big Data and Hadoop.
    • Facebook, which is a $5.1 billion company, has over 1 billion active users! It is Hadoop that enables Facebook to manage data of such magnitude.
    • Linkedin manages over 1 billion personalized recommendations every week, with the help of Hadoop’s MapReduce and HDFS features.
    • The Yahoo! Search Webmap is a Hadoop application that runs on over 10,000 core Linux cluster and generates the data that is widely used in each query of Yahoo! Web search.

  • What learning benefits do you get from Simplilearn’s training?

    At the end of Simplilearn’s training in the basics of Big Data and Hadoop, the participants will:
    • Understand the characteristics of Big Data
    • Describe the basics of Hadoop and HDFS architecture
    • List the features and processes of MapReduce
    • Learn the basics of Pig, Hive and HBase
    • Explore the commercial distributions of Hadoop
    • Understand the key components of the Hadoop ecosystem
    • Get introduced to Sqoop & ZooKeeper

  • What are the career benefits in-store for you?

    A good understanding of the basics of Big Data and Hadoop makes it easier to improve your analytic skills, thus increasing your career prospects in the Big Data analytics industry. According to Robert Half Technology, the average salary for a Hadoop certified Professional is in the range of $154,250.

    Top companies like Microsoft, Software AG, IBM, Oracle, HP, SAP, EMC2 and Dell have invested a huge $15 billion on data management and analytics, thereby increasing the number of opportunities for Big data & Hadoop certified professionals.

  • Who should do this course?

    Simplilearn’s ‘Introduction to Big data and Hadoop’ course is meant for professionals who intend to gain a basic understanding of Big Data and Hadoop. It is ideal for professionals in senior management who requires a theoretical understanding of how Hadoop can solve their Big Data problem.

Course preview

    • Lesson 1.0 - Introduction to Big Data and Hadoop

      29:37
      • 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

      29:59
      • 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

      00:09
      • Thank You
        00:09
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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.

Read more Read less
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.

FAQs

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