Big Data Management
This course prepares students to deal with large- scale collections of data as objects to be stored, searched over, selected, and transformed for use and reuse. It examines the underlying principles and technologies used to capture data, clean it, contextualize it, store it, and access it for a repurposed use. Data provenance is also examined to determine the trustworthiness of data.
At the end of the course, participants are able to:
1. Explain the processes in data pipeline.
2. Discuss database concepts and technologies for big data storage and retrieval.
3. Apply appropriate models, tools, and
4. Technologies to implement storage, search and retrieval systems for large-scale structured and unstructured information systems.
5. Analyse data provenance and data trustworthiness, and its role in sharing and reuse of data.
2. Introduction to Big Data
3. Big Data Issues: Data Provenance
4. Big Data Issues: Data Privacy and Trustworthy
5. Data Science with Big Data
6. Data Science Pipeline
7. Data Science Application
8. Big Data Management
9. Big Data Modelling: Data model overviews
10. Big Data Technology: Traditional database management
11. Big Data Technology: Introduction to NoSQL databases
12. Big Data Concept: Providing structure for unstructured data
Case Study Submission
13. Big Data Concept: Identification and ontologies
Group Project Submission
14. Big Data Challenges
Group Project Presentation
Dr Hoo Wai Lam,
Lecturer, Department of Information Systems,
Faculty of Computer Science & Information Technology
- Tuesday (6.00 pm - 9.00 pm)
Semester 2/2022 (Starting on March 2022)
- Certificate of Achievement (with assessment)
- Certificate of Completion (without assessment)
RM3,082(Certificate of Achievement)
RM2,618(Certificate of Completion)