Welcome to Big Data Management (BDM) class! We are thrilled to embark on this exciting learning journey together. Before our first class, there are a few important steps you need to take:
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Complete Information Form: Please fill in 🧑💻 your details in the provided Google Sheets document here.
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Create a GitHub Account: Ensure you have a GitHub
account by signing up at GitHub. -
Access Teaching Materials: All teaching materials will be available on my GitHub account. Please follow this link to access the materials.
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Fork and Star Repository: To kick off our first meeting, please fork and star the repository available here. We will be using this repository extensively.
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GitHub Usage for Course: Throughout this course, we will utilize GitHub for sharing materials, submitting tasks, projects, and more. Make sure you have a meaningful GitHub username associated with your account.
Please be sure to complete these tasks before our first class, as they are essential for our learning and collaboration.
Looking forward to an amazing and productive class!
This course provides a basic fundamental of big data architecture and management. Students will learn the big data processes and the current big data technologies that are available. Further, students will be exposed to the big data platform ecosystem for big data manipulation. The big data management will be explored for the best practice in managing and manipulating large amount of data. At the end of the course, students should be able to understand the architecture and management of big data and also can develop simple application of big data handling using particular platform in assignment.
- Understand the technology for managing, processing and manipulating large amount of data.
- Design big data platform demonstrating the implementation of big data applications.
- Discuss current technology that support for sustainability of the big data platform ecosystem.
- Student Information
- Course Information
- AWS Academy Cloud Foundations
- AWS Academy Cloud Architecting
- AWS Academy Data Engineering
- AWS Academy Machine Learning for Natural Language Processing
| Week | Topic |
|---|---|
| 1 | Introduction to Big Data and Big Data Analytics - Fundamentals and concepts of big data |
| 2 | Big Data Processing and Technology - Batch, real-time, and streaming processing. - Scalability, storage, sourcing challenges. |
| 3-4 | - ACID, BASE, and CAP theorem - Distributed File Processing & Map Reduce Processing |
| 5 | - Lambda Architecture |
| 6-7 | Relational Database (RDBMS) - Relational Data Modelling - Database design phases |
| 8 | Relational Database (RDBMS) - SQL programming (DDL, DML, CRUD Operation) |
| 9 | Relational Database (RDBMS) - SQL programming (Subqueries, Join Tables, Aggregate) |
| 10 | No SQL Database - Introduction to No SQL database - Semi-structured data Modelling (Key Value, Column Family, Document, and Graph) |
| 11-12 | No SQL database (Document-based Database) - Document-based data modelling - MongoDB query language |
| 13-14 | Cloud Technology - Introduction to Cloud - AWS Cloud (via AWS Learning Management System) |
| 15 | Project Presentation |
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