Course description

  • What is this course about?

    This 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

      29:23
      • 1 Introduction to Big Data and Hadoop
        00:21
      • 2 Objectives
        00:25
      • 3 Need for Big Data
        01:42
      • 4 Three Characteristics of Big Data
        00:34
      • 5 Characteristics of Big Data Technology
        01:52
      • 6 Appeal of Big Data Technology
        00:49
      • 7 Handling Limitations of Big Data
        00:49
      • 8 Introduction to Hadoop
        01:00
      • 9 Hadoop Configuration
        00:52
      • 10 Apache Hadoop Core Components
        00:35
      • 11 Hadoop Core Components—HDFS
        01:07
      • 12 Hadoop Core Components—MapReduce
        00:44
      • 13 HDFS Architecture
        01:12
      • 14 Ubuntu Server—Introduction
        00:51
      • 15 Hadoop Installation—Prerequisites
        00:26
      • 16 Hadoop Multi-Node Installation—Prerequisites
        00:28
      • 17 Single-Node Cluster vs. Multi-Node Cluster
        00:48
      • 18 MapReduce
        01:08
      • 19 Characteristics of MapReduce
        00:56
      • 20 Real-Time Uses of MapReduce
        01:00
      • 21 Prerequisites for Hadoop Installation in Ubuntu Desktop 12.04
        00:20
      • 22 Hadoop MapReduce—Features
        00:52
      • 23 Hadoop MapReduce—Processes
        00:47
      • 24 Advanced HDFS–Introduction
        00:47
      • 25 Advanced MapReduce
        00:54
      • 26 Data Types in Hadoop
        01:15
      • 27 Distributed Cache
        00:41
      • 28 Distributed Cache (contd.)
        00:39
      • 29 Joins in MapReduce
        00:43
      • 30 Introduction to Pig
        00:39
      • 31 Components of Pig
        00:59
      • 32 Data Model
        00:47
      • 33 Pig vs. SQL
        01:07
      • 34 Prerequisites to Set the Environment for Pig Latin
        00:19
      • 35 Summary
        00:55
    • Lesson 1.1 - Hive HBase and Hadoop Ecosystem Components

      29:46
      • 1 Hive, HBase and Hadoop Ecosystem Components
        00:22
      • 2 Objectives
        00:23
      • 3 Hive—Introduction
        00:54
      • 4 Hive—Characteristics
        01:20
      • 5 System Architecture and Components of Hive
        00:17
      • 6 Basics of Hive Query Language
        00:38
      • 7 Data Model—Tables
        00:32
      • 8 Data Types in Hive
        00:15
      • 9 Serialization and De serialization
        01:18
      • 10 UDF/UDAF vs. MapReduce Scripts
        00:47
      • 11 HBase—Introduction
        01:14
      • 12 Characteristics of HBase
        00:41
      • 13 HBase Architecture
        01:04
      • 14 HBase vs. RDBMS
        01:07
      • 15 Cloudera—Introduction
        00:44
      • 16 Cloudera Distribution
        01:07
      • 17 Cloudera Manager
        00:33
      • 18 Hortonworks Data Platform
        00:42
      • 19 MapR Data Platform
        00:43
      • 20 Pivotal HD
        00:52
      • 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
        01:25
      • 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
        00:53
      • 33 Apache Spark
        01:27
      • 34 Apache Ambari
        00:32
      • 35 Key Features of Apache Ambari
        00:51
      • 36 Hadoop Security—Kerberos
        00:53
      • 37 Summary
        00:47
    • Quiz

      • Quiz
    • Thank You

      00:08
      • Thank You
        00:08
    • Lesson 00 - Introduction

      05:27
      • 0.001 Course Introduction
        05:27
    • Lesson 01 - Introduction to Business Analytics

      09:52
      • 1.001 Introduction
        02:15
      • 1.002 What Is in It for Me
        00:10
      • 1.003 Types of Analytics
        02:18
      • 1.004 Areas of Analytics
        04:06
      • 1.5 Quiz
      • 1.006 Key Takeaways
        00:52
      • 1.007 Conclusion
        00:11
    • Lesson 02 - Formatting Conditional Formatting and Important Fuctions

      38:29
      • 2.001 Introduction
        02:12
      • 2.002 What Is in It for Me
        00:21
      • 2.003 Custom Formatting Introduction
        00:55
      • 2.004 Custom Formatting Example
        03:24
      • 2.005 Conditional Formatting Introduction
        00:44
      • 2.006 Conditional Formatting Example1
        01:47
      • 2.007 Conditional Formatting Example2
        02:43
      • 2.008 Conditional Formatting Example3
        01:37
      • 2.009 Logical Functions
        04:00
      • 2.010 Lookup and Reference Functions
        00:28
      • 2.011 VLOOKUP Function
        02:14
      • 2.012 HLOOKUP Function
        01:19
      • 2.013 MATCH Function
        03:13
      • 2.014 INDEX and OFFSET Function
        03:50
      • 2.015 Statistical Function
        00:24
      • 2.016 SUMIFS Function
        01:27
      • 2.017 COUNTIFS Function
        01:13
      • 2.018 PERCENTILE and QUARTILE
        01:59
      • 2.019 STDEV, MEDIAN and RANK Function
        03:02
      • 2.020 Exercise Intro
        00:35
      • 2.21 Exercise
      • 2.22 Quiz
      • 2.023 Key Takeaways
        00:53
      • 2.024 Conclusion
        00:09
    • Lesson 03 - Analyzing Data with Pivot Tables

      19:32
      • 3.001 Introduction
        01:47
      • 3.002 What Is in It for Me
        00:22
      • 3.003 Pivot Table Introduction
        01:03
      • 3.004 Concept Video of Creating a Pivot Table
        02:47
      • 3.005 Grouping in Pivot Table Introduction
        00:24
      • 3.006 Grouping in Pivot Table Example 1
        01:42
      • 3.007 Grouping in Pivot Table Example 2
        01:57
      • 3.008 Custom Calculation
        01:14
      • 3.009 Calculated Field and Calculated Item
        00:25
      • 3.010 Calculated Field Example
        01:22
      • 3.011 Calculated Item Example
        02:52
      • 3.012 Slicer Intro
        00:35
      • 3.013 Creating a Slicer
        01:22
      • 3.014 Exercise Intro
        00:58
      • 3.15 Exercise
      • 3.16 Quiz
      • 3.017 Key Takeaways
        00:35
      • 3.018 Conclusion
        00:07
    • Lesson 04 - Dashboarding

      32:07
      • 4.001 Introduction
        01:18
      • 4.002 What Is in It for Me
        00:18
      • 4.003 What is a Dashboard
        00:45
      • 4.004 Principles of Great Dashboard Design
        02:16
      • 4.005 How to Create Chart in Excel
        02:26
      • 4.006 Chart Formatting
        01:45
      • 4.007 Thermometer Chart
        03:32
      • 4.008 Pareto Chart
        02:26
      • 4.009 Form Controls in Excel
        01:08
      • 4.010 Interactive Dashboard with Form Controls
        04:13
      • 4.011 Chart with Checkbox
        05:48
      • 4.012 Interactive Chart
        04:37
      • 4.013 Exercise Intro
        00:55
      • 4.017 Key Takeaways
        00:34
      • 4.018 Conclusion
        00:06
    • Lesson 05 - Business Analytics With Excel

      25:48
      • 5.001 Introduction
        02:12
      • 5.002 What Is in It for Me
        00:24
      • 5.003 Concept Video Histogram
        05:18
      • 5.004 Concept Video Solver Addin
        05:00
      • 5.005 Concept Video Goal Seek
        02:57
      • 5.006 Concept Video Scenario Manager
        04:16
      • 5.007 Concept Video Data Table
        02:03
      • 5.008 Concept Video Descriptive Statistics
        01:58
      • 5.009 Exercise Intro
        00:52
      • 5.11 Quiz
      • 5.012 Key Takeaways
        00:39
      • 5.013 Conclusion
        00:09
    • Lesson 06 - Data Analysis Using Statistics

      31:57
      • 6.001 Introduction
        01:51
      • 6.002 What Is in It for Me
        00:21
      • 6.003 Moving Average
        02:50
      • 6.004 Hypothesis Testing
        04:20
      • 6.005 ANOVA
        02:47
      • 6.006 Covariance
        01:56
      • 6.007 Correlation
        03:38
      • 6.008 Regression
        05:15
      • 6.009 Normal Distribution
        06:49
      • 6.010 Exercise1 Intro
        00:34
      • 6.11 Exercise 1
      • 6.012 Exercise2 Intro
        00:17
      • 6.13 Exercise 2
      • 6.014 Exercise3 Intro
        00:19
      • 6.15 Exercise 3
      • 6.16 Quiz
      • 6.017 Key Takeaways
        00:52
      • 6.018 Conclusion
        00:08
    • Lesson 07 - Power BI

      14:01
      • 7.001 Introduction
        01:17
      • 7.002 What Is in It for Me
        00:18
      • 7.003 Power Pivot
        04:16
      • 7.004 Power View
        02:36
      • 7.005 Power Query
        02:45
      • 7.006 Power Map
        02:06
      • 7.7 Quiz
      • 7.008 Key Takeaways
        00:32
      • 7.009 Conclusion
        00:11
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Exam & certification

  • What qualifications do you need?

    There are no prerequisites for this course.

FAQs

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    Please join our Live Chat for instant support, call us, or Request a Call Back to have your query resolved.

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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.