Upcoming Batch
21 to 25 Mar 2021 Online ‘Live’9:30am to 5:30pm Singapore Timezone
4 Sessions / 32-Hours Apply Now
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19 to 22 Apr 2021 Online ‘Live’9:30am to 5:30pm Singapore Timezone
4 Sessions / 32 Hours Apply Now
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18 to 21 May 2021 Online ‘Live’9:30am to 5:30pm Singapore Timezone
4 Sessions / 32 Hours Apply Now
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Course Information
- Duration: 4-Day / 32 Hours
- Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination
- Who Should Attend: Data Analyst, Finance Analyst, HR Analyst, Software Engineers, Database Administrator, CIO or Anyone interested in pursuing a career in Big Data, Data Analytics, and Data Engineering
Course Objective
Acquiring advanced knowledge and skills on how to use Hadoop in Big Data to identify correlation and causation statistically valid models as part of their organisation strategic decision making and planning.
Pre-Requisite
It is preferred that participants successfully completed and pass Data Analytics Essentials (DAE)
Examination
Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Big Data and Hadoopbased on the syllabus covered
Module 1
Data Types and Relational Database Management System (RDBMS)
Topics Covered
- Data Types & RDBMS Concepts
- Structured Query Language – SQL Basics
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- Data Warehousing Concepts
- Data Modeling Concepts
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Module 2
Introduction to Big Data and Hadoop
Topics Covered
- Introduction to Big Data and Hadoop
- Hadoop Architecture
- Hadoop Deployment
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- Hadoop Troubleshooting
- Introduction to Hadoop Distributed File System (HDFS)
- Introduction to MapReduce
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Module 3
Processing Data in Hadoop
Topics Covered
- Overview on MapReduce
- When to Use MapReduce
- Introduction to Spark
- Components and Concept of Spark
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- Understanding Abstraction
- Working with Pig
- Overview on Hive
- Apache Hive – Hive Query Language
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Module 4
Fundamentals to NoSQL Data Management for Big Data
Topics Covered
- Introduction to NoSQL
- Concepts of NoSQL
- Key-Value Stores
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- Document Stores
- Object Data Stores
- Graph Databases
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Module 5
Real-Time Data Processing with Hadoop
Topics Covered
- Understand Stream Processing
- Introduction to Apache Storm
- Understanding Storm Architecture and Topologies
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- Integration Storm with HDFS
- Integration Storm with HBase
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Module 6
Spark Streaming
Topics Covered
- Overview on Spark Streaming
- Spark Streaming with Simple Count
- Spark Streaming with Multiple Inputs
- Maintaining State
- Windowing in Spark Streaming
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- Streaming vs. ETL Code
- Batch Analytics with Spark
- SparkSQL and DataFrame
- DataFrame APIs and SQL API
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Module 7
Visualizing in Big Data
Topics Covered
- Big Data Visualization Tools
- Quick Overview on the Different Chart Types
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- Using Python to Visualize Data
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Advanced Big Data Professional (ABDP) involves rigorous usage of real-time case studies, hands-on exercises and group discussions
What Past Participants Say
The case study discussion during the course by CASUGOL trainer provides participant with the much required insights on the subject matter.
Vernon Tan
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CASUGOL training provide participants with lots of real-time hands-on activities. Participants also received personal coaching in class by CASUGOL trainers with lots of experience.
Savita K. Sugathan
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Why CASUGOL
Customization of Programs for specific industry, organisation, government agencies, statutory boards.
Flexible programmes designed to cater to the individual needs of participants, whether for professional upskilling, or for general interest.
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Benefit from contribution from leading Industry Experts, Academics, and Researchers from across the world.
Opportunities for employers to develop their workforce and for individuals to enhance their career.
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Dynamic learning environment that providing participants with professional networking opportunity.
Online support for participants after the training. |
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