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.

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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.