Big Data and Hadoop Training

Big Data and Hadoop Training

Become an analytics and Big Data Specialist and Data Scientist every company wants. Learn both Hadoop and Big Data technologies

course at a glance

  • Date : 20 Jul - 12 Oct 2018
  • No. of Classes/ Sessions : 12
  • Total Hours : 48
  • Last Date of Registration : 19 Jul 2018
  • Class Schedule :
    • Friday - 2.30pm - 6.30pm
  • venue : RH Home Center, Suite No. 539, Level: 5, 74/B/1 Green Road, Tejgaon, Dhaka - 1205.

Price: TK. 10,000

This training is jointly organized by BITM & Business Accelerate BD Ltd.
Training will be held in  Business Accelerate BD Ltd. 


COURSE CURRICULUM

Section: 1
Introduction.
1. Introduction

Section: 2
Big Data at a Glance
2. What is data?
3. What is Big Data?
4. Data Sources of Big Data part 1
5. Data Sources of Big Data part 2
6. Traditional Analytics vs Big Data Analytics.
7. Big Data Customers-Many Industrial Domains.

Section: 3
Big Data Attributes Challenges.
8. Volume.
9. Variety.
10. Velocity.
11. Veracity.

Section: 4
Getting Started with Hadoop.
12. Hadoop History.
13. Hadoop Concepts.
14. Hadoop Ecosystem.
15. Hadoop Core Components.
16. Hadoop Distributions.

Section: 5
HDFS architecture and Concepts.
17. HDFS-Blocks-File Splits.
18. HDFS Write Operation.
19. HDFS-Hadoop-2.x-Architecture-part 1.
20. HDFS-Hadoop-2.x-Architecture-part 2.

Section: 6
Understanding MapReduce.
21. MapReduce Components.
22. Understand MapReduce Flow.
23. Client Communication.
24. NEED OF YARN.
25. HDFS Architecture.
26. NodeManager
27. Hadoop Cluster Modes.
28. Secondary Namenode.

Session: 7
Programming Hadoop with Hive and Hbase.
29. Understanding Hive
30. Understanding Hbase
31. Using relational data stores with Hadoop
32. Using non-relational data stores with Hadoop

Session: 8
Programming Hadoop with Pig
33. Understanding Pig
34. Programming Hadoop with Pig

Session: 9
Programming Hadoop with Spark
35. Spark Basics
36. Spark Libraries
37. Spark Streaming
38. Using Spark
39. Analyzing Streams of Data

Session:10
Understanding Hadoop Libraries and Workflows and Connectors
40. Introducing Oozie
41. Building a workflow with Oozie
42. Introducing Sqoop
43. Importing data with Sqoop
44. Introducing Flume
45. Introducing ZooKeeper
46. Using ZooKeeper to coordinate workflows
47. Introducing Impala
48. Using Impala
49. Introducing Mahout
50. Introducing Storm

Session: 11
Data Visualization and Real world System
51. Visualizing Hadoop Output with Tools
52. Designing Real-World Systems

Section: 12
Hadoop Installation and Configuration.
53. Hadoop 2.7.3 Installation-part1
54. Hadoop 2.7.3 Installation-part2
55. Hadoop 2.7.3 Configuration Files.
56. Hadoop Basic Commands.

Section: 13
Project 1: Customer Support Analysis Using MapReduce
57. Overview
58. Implementation of Scenario -1 in MapReduce
59. Implementation of Scenario -1 in MapReduce -Continuous...
60. Implementation of Scenario -2 in MapReduce
61. Implementation of Scenario -3 in MapReduce

Section: 14
Project 2- Video Data Analysis Using MapReduce.
62. Problem Statement.
63. Understanding Problem Statement
64. Data Preparation and Understanding
65. Basics of Big Data
66. MapReduce
67. MapReduce-Programming To Process the Scenario for Analysis part-2
68. MapReduce-Top 10 Highest Rated Videos
69. MapReduce-Top 10 Most Viewed Videos
70. MapReduce-How many people Age less 18 years uploaded Videos
71. MapReduce-Different Scenarios for Videos Analysis

Curriculum

Theory Mastering Hadoop and related tools with real-time data processing using Spark,Pig,Hive,Impala 19 Hrs
Practical Customer Support Analysis Using MapReduce, Video Data Analysis Using MapReduce. 20 Hrs
Project #1 Customer Complaints Analysis 3 Hrs
Project #2 Analyze Loan Dataset 3 Hrs
Project #3 Enhance Customer Experience Management 3 Hrs

Tentative Class Start

20th July, 2018

Available Seat

10 / 16

who can join

Market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Here are the few Professional IT groups, who are continuously enjoying the benefits moving into Big data domain:
 
  • Software Developers and Architects
  • BI /ETL/DW professionals
  • Analytics Professionals
  • Senior IT professionals
  • Testing and Mainframe professionals
  • Data Management Professionals
  • Business Intelligence Professionals
  • Project Managers
  • Aspiring Data Scientists

Graduates looking to build a career in Big Data Analytics

Meet the Instructor