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Introduction to Big Data and Hadoop

Course Summary

Step into the world of Big Data with an introduction to Hadoop and its ecosystem components.


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    Course Syllabus


    Course preview

    Introduction to Big Data and Hadoop

    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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Course Fee:
USD 99

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Development & Implementations and Data & Information Management Community

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