Big Data and Hadoop Administrator Certification Training

Big Data and Hadoop Administrator Certification Training

547,500.00

 

Big Data and Hadoop Administrator course offered by JK michaels provides a hands-on experience to install, configure, and manage the Apache Hadoop platform. The course covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. In addition, it also focuses on the whole ecosystem of Big Data and Hadoop.

Description

Big Data and Hadoop Administrator Certification Training Overview

 

  • JK Michaels Big Data and Hadoop Administrator certification training is an ideal course package for every aspiring professional who wants to make his/her career in the Big Data sector. Hadoop administrator will be able to build and maintain the infrastructure which is needed to store and process big data.Big Data and Hadoop Administrator course offered by JK michaels provides a hands-on experience to install, configure, and manage the Apache Hadoop platform. The course covers topics to deploy, manage, monitor, and secure a Hadoop Cluster. In addition, it also focuses on the whole ecosystem of Big Data and Hadoop.

    By the end of the training participant will have the knowledge and skills to become a successful Hadoop Architect.

  • Big Data and Hadoop Administrator Certification Training Objectives

  • At the end of JK Michaels training in Big Data and Hadoop Administrator, the participants will be able to:
    • Create and maintain Big Data and Hadoop ecosystem
    • Develop advanced cluster configuration features
    • Understand the Hadoop Distributed File System
    • Understand and work on MapReduce and YARN
    • Understand important Hadoop components and ecosystem components like Pig, Hive, Impala, Ganglia, Nagios, Sqoop and others
    • Understand Hadoop’s Security system

KEY FEATURES|Big Data and Hadoop Administrator Certification Training

  • 40 Hrs of Lab Exercises with proprietary VM
  • 27 Hrs of High Quality e-Learning content
  • Taught via Real-life case studies & world examples
  • 4 Simulation Exams
  • 48 End of Chapter Quizzes
  • Downloadable e-Book Included
  • Get Certified as a Hadoop Administrator

Course Outlines

Lesson 00 – Course Introduction9:24
0.1 Course Introduction 1.19
  • 0.2 Key FeatureS 1.10
  • 0.3 Course Objectives 1.31
  • 0.4 Course Overview1:46
  • 0.5 Course Overview (contd.)1:40
  • 0.6 Course Prerequisites1:32
  • 0.7 Value to Professionals1:46
  • 0.8 Lessons Covered1:17
  • 0.9 Concludes
  • Lesson 01 – Introduction to Big Data and Hadoop40:22
    • 1.1 Introduction to Big Data and Hadoop1:15
    • 1.2 Objectives1:21
    • 1.3 Introduction2:18
    • 1.4 Types Of Data1:39
    • 1.5 Characteristics Of Big Data1:39
    • 1.6 Appeal Of Big Data Technology1:48
    • 1.7 Business Benefits Of Big Data Technology2:39
    • 1.8 Business Benefits Of Big Data Technology (contd.)2:20
    • 1.9 Traditional IT Analytics Approach1:37
    • 1.10 Traditional IT Analytics Approach (contd.)1:30
    • 1.11 Big Data Technology Platform For Discovery And Exploration1:45
    • 1.12 Big Data Technology Platform For Discovery And Exploration (contd.)1:38
    • 1.13 Big Data Technology Capabilities1:30
    • 1.14 Big Data And Use Cases1:54
    • 1.15 Challenges Of Big Data1:34
    • 1.16 Introduction To Hadoop1:58
    • 1.17 Hadoop And Traditional Rdbms2:34
    • 1.18 History And Milestones Of Hadoop2:38
    • 1.19 Hadoop Core Services2:23
    • 1.20 Hdfs Architecture1:47
    • 1.21 Organizations Using Hadoop1:41
    • 1.22 Quiz0:0
    • 1.23 Summary2:4
    • 1.24 Conclusion
  • Lesson 02 – Planning Hadoop Cluster57:12
    • 2.1 Planning Hadoop Cluster1:15
    • 2.2 Objectives1:26
    • 2.3 Overview of Hadoop Cluster2:45
    • 2.4 Architecture of Hadoop Cluster1:46
    • 2.5 Architecture of Hadoop Cluster (contd.)1:26
    • 2.6 Architecture of Hadoop Cluster-Illustration1:58
    • 2.7 Workflow of Hadoop Cluster1:35
    • 2.8 HDFS Writes2:10
    • 2.9 HDFS Writes-Example1:45
    • 2.10 Preparing for HDFS Writes3:35
    • 2.11 Pipelined HDFS Write1:49
    • 2.12 NameNode2:10
    • 2.13 NameNode Functionality2:23
    • 2.14 Replicating Missing Replicas1:44
    • 2.15 HDFS Reads1:53
    • 2.16 Unbalanced Cluster2:32
    • 2.17 Balancer Utility2:35
    • 2.18 Factors for Planning Hadoop Cluster2:42
    • 2.19 Hardware and Network Configurations-Slave2:37
    • 2.20 Hardware and Network Configurations-Master1:58
    • 2.21 Network Topology for Hadoop Cluster2:11
    • 2.22 Network Topology for Hadoop Cluster (contd.)2:23
    • 2.23 Topology and Components of Hadoop Cluster1:49
    • 2.24 Cluster Management Commands1:54
    • 2.25 Cluster Management-Illustration1:46
    • 2.26 Quiz0:0
    • 2.27 Summary1:51
    • 2.28 Conclusion
  • Lesson 03 – Hadoop Installation and Configuration105:2
    • 3.1 Hadoop Installation and Configuration1:18
    • 3.2 Objectives1:26
    • 3.3 Ubuntu Server-Introduction1:50
    • 3.4 Installation of Ubuntu Server 12.41:46
    • 3.5 Business Scenario1:56
    • 3.6 Demo Install Ubuntu Server 12.44:9
    • 3.7 Demo Summary1:27
    • 3.8 Hadoop Installation2:35
    • 3.9 Hadoop Installation-Prerequisites1:23
    • 3.10 Hadoop Installation-Step 11:30
    • 3.11 Hadoop Installation-Step 22:2
    • 3.12 Hadoop Installation-Step 31:23
    • 3.13 Hadoop Installation-Step 41:21
    • 3.14 Hadoop Installation-Step 51:14
    • 3.15 Hadoop Installation-Step 61:19
    • 3.16 Hadoop Installation-Step 71:23
    • 3.17 Hadoop Installation-Step 7 (contd.)1:21
    • 3.18 Hadoop Installation-Step 81:26
    • 3.19 Hadoop Installation-Step 8 (contd.)1:15
    • 3.20 Hadoop Installation-Step 8 (contd.)1:13
    • 3.21 Hadoop Installation-Step 91:23
    • 3.22 Hadoop Installation-Step 9 (contd.)1:33
    • 3.23 Hadoop Installation-Step 101:19
    • 3.24 Hadoop Installation-Step 10 (contd.)1:18
    • 3.25 Hadoop Installation-Step 111:37
    • 3.26 Hadoop Installation-Step 121:37
    • 3.27 Hadoop Installation-Step 12 (contd.)1:33
    • 3.28 Demo Hadoop 1 . 0 in Ubuntu Server 12.48:19
    • 3.29 Demo Summary2:15
    • 3.30 Hadoop Multi-Node Installation-Prerequisites1:27
    • 3.31 Steps for Hadoop Multi-Node Installation1:48
    • 3.32 Hadoop Multi-Node Installation-Steps 1 and 21:16
    • 3.33 Hadoop Multi-Node Installation-Step 31:21
    • 3.34 Hadoop Multi-Node Installation-Step 3 (contd.)1:42
    • 3.35 Hadoop Multi-Node Installation-Step 41:53
    • 3.36 Hadoop Multi-Node Installation-Step 4 (contd.)1:21
    • 3.37 Hadoop Multi-Node Installation-Step 4 (contd.)1:26
    • 3.38 Single-Node Cluster vs Multi-Node Cluster1:42
    • 3.39 Demo Create a Clone of Hadoop Virtual Machine1:59
    • 3.40 Demo Summary1:5
    • 3.41 Demo Perform Clustering of the Hadoop Environment8:50
    • 3.42 Demo Summary2:0
    • 3.43 Demo Install Hadoop 2. in Ubuntu Server 12.49:2
    • 3.44 Demo Summary2:0
    • 3.45 Quiz0:0
    • 3.46 Summary1:49
    • 3.47 Conclusion
  • Lesson 04 – Advanced Cluster Configuration Features38:32
    • 4.1 Advanced Cluster Configuration Features1:17
    • 4.2 Objectives1:33
    • 4.3 Hadoop Configuration Overview2:10
    • 4.4 Types of Configuration Files1:54
    • 4.5 Important Configuration Files1:13
    • 4.6 Important Configuration Files (contd.)1:38
    • 4.7 Configuration Parameters and Values1:44
    • 4.8 Hadoop Cluster Configuration Parameters and Values2:43
    • 4.9 Hadoop Cluster Configuration Parameters and Values (contd.)1:8
    • 4.10 Hadoop Map Reduce Configuration Parameters and Values1:20
    • 4.11 Prerequisites for Installing Hadoop1:48
    • 4.12 Hadoop Environment Setup2:24
    • 4.13 Include and Exclude Configuration Files1:58
    • 4.14 Business Scenario1:32
    • 4.15 Demo-Configuration of Hadoop Settings7:26
    • 4.16 Demo summary1:45
    • 4.17 Quiz0:0
    • 4.18 Summary2:2
    • 4.19 Conclusion
  • Lesson 05 – Hadoop Distributed File System81:30
    • 5.1 Hadoop Distributed File System1:17
    • 5.2 Objectives1:35
    • 5.3 Introduction to Hadoop Distributed File System2:25
    • 5.4 Goals of HDFS2:25
    • 5.5 HDFS Architecture2:5
    • 5.6 Design of HDFS3:16
    • 5.7 HDFS Concept3:30
    • 5.8 Hadoop Storage Mechanism1:59
    • 5.9 Measures of Capacity Execution1:59
    • 5.10 HDFS Storage Architecture Heterogeneous Storage2:18
    • 5.11 HDFS Storage Architecture Illustration1:34
    • 5.12 HDFS Rack Awareness2:32
    • 5.13 HDFS Writes Example1:46
    • 5.14 HDFS Reads1:55
    • 5.15 Important Commands of HDFS1:15
    • 5.16 Important Commands of HDFS (contd.)1:14
    • 5.17 Types of HDFS Commands1:24
    • 5.18 User Commands1:14
    • 5.19 User Commands (contd.)1:9
    • 5.20 Administrator Commands1:9
    • 5.21 Administrator Commands (contd)1:13
    • 5.22 Business Scenario1:32
    • 5.23 Demo-HDFS5:56
    • 5.24 Demo Summary1:30
    • 5.25 Introduction to Sqoop2:23
    • 5.26 Sqoop Illustration1:29
    • 5.27 How Sqoop Works1:56
    • 5.28 Prerequisites for Sqoop Installation1:41
    • 5.29 Installing and Configuring Sqoop1:21
    • 5.30 Installing and Configuring Sqoop (contd.)1:12
    • 5.31 Installing and Configuring Sqoop (contd.)1:14
    • 5.32 Importing Data from MySQL1:17
    • 5.33 Business Scenario1:38
    • 5.34 Demo-Install Sqoop10:32
    • 5.35 Demo Summary1:16
    • 5.36 Quiz0:0
    • 5.37 Summary1:54
    • 5.38 Conclusion
  • Lesson 06 – Overview of MapReduce and YARN38:28
    • 6.1 Overview of MapReduce and YARN1:17
    • 6.2 Objectives1:32
    • 6.3 MapReduce Introduction1:59
    • 6.4 Concepts of MapReduce1:38
    • 6.5 History of MapReduce1:39
    • 6.6 Automatic Parallel Execution in MapReduce2:41
    • 6.7 MapReduce Framework2:5
    • 6.8 How Map and Reduce Work Together1:28
    • 6.9 MapReduce Example1:41
    • 6.10 Workflow of MapReduce1:55
    • 6.11 Characteristics of MapReduce1:53
    • 6.12 Development and Libraries of MapReduce2:31
    • 6.13 MapReduce Failure and Recovery1:43
    • 6.14 Introduction to YARN1:47
    • 6.15 Need for YARN1:25
    • 6.16 Benefits of YARN1:33
    • 6.17 YARN Architecture2:1
    • 6.18 YARN Architecture Illustration2:53
    • 6.19 YARN Daemons1:17
    • 6.20 YARN Installation1:23
    • 6.21 YARN Configuration1:25
    • 6.22 Working with YARN and YARN Web UI1:37
    • 6.23 Working with YARN and YARN Web UI (contd.)1:27
    • 6.24 Quiz0:0
    • 6.25 Summary1:44
    • 6.26 Conclusion
  • Lesson 07 – Important Hadoop Components61:6
    • 7.1 Important Hadoop Components1:21
    • 7.2 Objectives1:22
    • 7.3 Hive2:4
    • 7.4 Hive vs. Other Traditional Databases1:53
    • 7.5 Hive Data Types1:34
    • 7.6 Prerequisites for Hive1:44
    • 7.7 Installing Hive1:25
    • 7.8 Installing Hive from Tarball2:42
    • 7.9 Configuring Hive2:36
    • 7.10 Hive site1:47
    • 7.11 Hive default . xml . template2:18
    • 7.12 Log Files3:1
    • 7.13 Hive Configuration Variables1:19
    • 7.14 Hive Configuration Variables (contd.)1:11
    • 7.15 Hive Configuration Variables Used to Interact with Hadoop1:22
    • 7.16 Hive Configuration Variables Used to Interact with Hadoop (contd.)1:13
    • 7.17 Business Scenario1:30
    • 7.18 Demo-Install Hive4:44
    • 7.19 Demo summary1:30
    • 7.20 Pig2:14
    • 7.21 Prerequisites for Pig1:36
    • 7.22 Installing Pig2:43
    • 7.23 Useful Commands for Pig1:20
    • 7.24 Configuring Pig1:57
    • 7.25 Business Scenario1:34
    • 7.26 Demo-Install Pig4:36
    • 7.27 Demo Summary1:30
    • 7.28 Impala2:6
    • 7.29 Installing and Configuring Impala1:48
    • 7.30 Quiz0:0
    • 7.31 Summary1:53
    • 7.32 conclusion
  • Lesson 08 – Hadoop Administration and Maintenance39:56
    • 8.1 Hadoop Administration and Maintenance1:15
    • 8.2 Objectives1:45
    • 8.3 Structural NameNode Formation and Naming Conventions1:59
    • 8.4 Structural DataNode Formation and Naming Conventions1:29
    • 8.5 File System Image and Edit Log2:36
    • 8.6 Checkpoint Procedure2:24
    • 8.7 The Checkpoint Procedure (contd.)1:47
    • 8.8 NameNode Failure and Recovery Procedure1:51
    • 8.9 Safe Mode1:54
    • 8.10 Metadata and Data Backup2:3
    • 8.11 Problems for Hadoop Administrators2:53
    • 8.12 Problems for Hadoop Administrators (contd.)2:13
    • 8.13 Solutions for Problems3:2
    • 8.14 Adding Nodes2:1
    • 8.15 Adding Nodes (contd.)1:45
    • 8.16 Removing Nodes3:5
    • 8.17 Quiz0:0
    • 8.18 Summary2:17
    • 8.19 Conclusion
  • Lesson 09 – Hadoop Ecosystem Components73:14
    • 9.1 Hadoop Ecosystem Components1:15
    • 9.2 Objectives1:44
    • 9.3 Overview of Ganglia1:44
    • 9.4 Components of Ganglia2:2
    • 9.5 Installation of Ganglia for Hadoop Server1:21
    • 9.6 Using Ganglia for Graphs1:48
    • 9.7 Using Ganglia for Graphs (contd)1:43
    • 9.8 Overview of Nagios2:7
    • 9.9 Installing Nagios1:24
    • 9.10 Installing Nagios Building from Source Method1:51
    • 9.11 Configuring Nagios for-Hadoop Alerts1:45
    • 9.12 Configuring Nagios for Hadoop Alerts (contd.)1:14
    • 9.13 Introduction to Sqoop1:56
    • 9.14 Advantages of Sqoop1:36
    • 9.15 Installing and Configuring Sqoop2:30
    • 9.16 Installing and Configuring Sqoop (contd.)2:14
    • 9.17 Importing Data from MySql to Hive using Sqoop1:53
    • 9.18 Other Ecosystem Components1:21
    • 9.19 Oozie1:45
    • 9.20 How Oozie Works1:48
    • 9.21 Avro1:51
    • 9.22 Thrift1:48
    • 9.23 Rest2:25
    • 9.24 Mahout1:44
    • 9.25 Apache Cassandra1:43
    • 9.26 Cassandra (contd.)1:43
    • 9.27 Yarn1:38
    • 9.28 MR21:43
    • 9.29 Hadoop Security1:58
    • 9.30 Kerberos and Hadoop1:43
    • 9.31 Importance of Hadoop Security2:23
    • 9.32 Hadoop Security System Concepts1:21
    • 9.33 Hadoop Integral Security Layer Authentication2:29
    • 9.34 Hadoop Integral Security Layer Authorization2:2
    • 9.35 Hadoop Integral Security Layer Encryption1:56
    • 9.36 OS Layer Security2:25
    • 9.37 Data Transfer and Integration Layer Security2:22
    • 9.38 Data Transfer and Integration Layer Security (contd.)2:9
    • 9.39 What is Kerberos and How it Works2:20
    • 9.40 Configuring Kerberos Security1:29
    • 9.41 Quiz0:0
    • 9.42 Summary1:59
    • 9.43 Summary (contd)1:49
    • 9.44 Thank You

Who Should Attend?

  • Who should do this course?

    JK Michaels Big Data and Hadoop Administrator course is suitable for professionals aspiring for a career in Big Data using Apache Hadoop, and individuals who intend to design, deploy, and maintain Hadoop clusters. System administrators, Developers, Architects, IT professionals, Analytics professionals, and experts are also the key beneficiaries. It is suitable for participants who are

    • Aspiring to be in fast growing career of Big Data
    • Looking for a more challenging position
    • Aiming to get into a more skillful role

What are the career benefits in-store for you?

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

    • The certification makes you ride the Big data wave, enhances your analytics skills and helps you to land in job roles like Hadoop Architect, Data Scientist, Hadoop Developer,  Hadoop Tester.
    • 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.
    • Certified analysts earn $117,000 in comparison to their non-certified peers.
    • Certified Big data professionals with Hands-on exposure to industry relevant tools have a growing career graph.

EXAM & CERTIFICATION

EXAM & CERTIFICATION

  • How do I become Certified Big Data & Hadoop Administrator?

    Participants get certified in Big Data & Hadoop by clearing the online examination with a minimum score of 80%.

What are the prerequisites for the course?

  • What are the prerequisites for the course?

    Fundamental knowledge of any programming language and Linux environment. Participants should know how to navigate and modify files within a Linux environment. Existing knowledge of Hadoop & Java is not required.