What Our Learners Say
Got an hands on experience in digital transformation especially on new trending and revolutionary technologies like AI,ML,Cyber security, IOT, Big data analytics, etc... nice experience and learned a more detailed knowledge I learnt Digital transformation course which is very iseful Nice session and very interactive staff The course was good and helpful The Lecture class was good and the lecturer is also expert in the topic 
Upcoming Batches
| Schedule |
Time (SGT / UTC +8) |
Sessions |
Date |
| Full-Time |
9:30am to 5:30pm
(Daily) |
5-Sessions |
8 to 12 Nov | 10 to 14 Jan | 14 to 18 Mar |
| Register Here
|
Course Information
- Duration: 5 Day / 40 Hours
- Certification: Participants will receive a Certificate of Competency upon successfully completing the course and passing the examination
- Who Should Attend: CIO, CTO, CISO, Information Specialist, Data Analysis, Data Scientist, Information Analysis, Marketing, HR, and Anyone interested in acquiring the advanced knowledge and skills in Big Data and NoSQL.
Course Objective
• Acquire the essential knowledge on Big Data, and NoSQL and its application in organizations.
Learn the different NoSQL databases, HBase, Cassandra, Redis Fit, and Hadoop Distributed File System
Pre-Requisite
No prior experience or technical knowledge required
Examination
Participants are required to attempt an examination of course to test students’ knowledge and skills related to BigData, NoSQL, and HDFS based on the syllabus covered.
Module 1
Introduction to NoSQL
Topics Covered
- Overview on NoSQL
- Consistency vs Availability
- Atomicity, Consistency, Isolation and Durability (ACID) in NoSQL
- CAP Theorem
- BASE
|
- Hash vs. Range Partition
- In-place Updates verses Appends
- Row vs. Column vs. Column-Family Storage Models
- Strongly versus Loosely Enforced Schemas
|
Module 2
Introduction to Big Data
Topics Covered
- What is Big Data?
- Types and Sources of Big Data
- Understanding Big Data Mining
|
- Technical Specifications of a Big Data Platform
- Big Data with Hadoop
|
Module 3
Processing Data with Hadoop and MapReduce
Topics Covered
- Fundamentals of Hadoop
- Hadoop Architecture and Deployment
- What is Hadoop Distributed File System (HDFS)
- The Hadoop Ecosystem
|
- YARN Architecture
- Overview on MapReduce
- Understanding MapReduce Framework and Architecture
- Inputting Splits in MapReduce
|
Module 4
Working with Hive
Topics Covered
- Introduction to Hive
- Common Hive Datatypes (Array, Map, Struct)
- Hive Functions (Collection, Conditional, String, Data, Mathematics)
- Joins, Multi Joins and Map Side Joins in Hive
|
- Working with Parquet and Fixed File Format
- Partitioning and Bucketing
- Hive Windows Function
- Sqoop Import and Export
|
Module 5
HBase
Topics Covered
- HBase Overview
- HBase Architecture
- Reads and Write with HBase
- System Trade-Offs
|
- Logical and Physical Data Models
- Interaction with HBase using HBase Shell
- Interacting with HBase using HBase Client API
|
Module 6
Apache Cassandra
Topics Covered
- Introduction to Cassandra
- Key Components of Cassandra
- Understanding Cassandra Architecture
- Cassandra Anti-patterns
|
- Hardware Selection, Configuration and Installation in Cassandra
- Node Configuration in Cassandra
- Running Cassandra
- Working with Cassandra
|
Module 7
Redis
Topics Covered
- Introduction to Redis
- Data Storage in Redis
- Installing, Configuring and Tuning Redis
- Data Types in Redis (Sets, Sorted Sets, Bitmaps, HyperLogLogs)
- Building Foundation, Optimizing with Hashes, Adding Uniqueness
|
- Commands in Redis
- Security Techniques for Redis
- Persistence, Replication, Partitioning, Automatic Sharding
- Redis Cluster and Redis Sentinel
|
Module 8
MongoDB
Topics Covered
- Introduction to MongoDB
- Installation and Configuration of MongoDB
- MongoDB Data Types
- Data Models in MongoDB
|
- MongoDB Indexing
- Replication and Sharding in MongoDB
- Storing of Large Data in MongoDB
|
NoSQL Essentials (NSE) involves rigorous usage of real-time case studies, hands-on exercises and group discussion
What Past Participants Say
The examples and cases shared in class are delivered in a clear, structured and easy to understand manner. It provide me with confidence to kickstart my own Machine Learning project.
Falhuddin Bin Nurdin
|
|
This course provide me with the detailed information required and essential tips how to explore more into the subject. The trainer is very helpful throughout the course. With his encouragement, I can understand the topics with ease even when I am not experience in programming.
Shalini Karthik
|
|
|
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.
|
|
|
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.
|
|
|
Dynamic learning environment that providing participants with professional networking opportunity.
Online support for participants after the training. |
|
Explore More Courses
Need more information?
Let us help if you are planning to advance your career and further your education. Request for more information.
Request for more
|
