IDTS5103 - Big Data Mining
Overview
This course provides comprehensive knowledge and practical skills in designing, implementing, and managing data warehouse systems and business intelligence solutions for organizational decision-making. The course focuses on enterprise data integration, multidimensional data modelling, analytical processing, reporting systems, and visualization technologies used in modern business environments.
Students will learn fundamental and advanced concepts in data warehousing including ETL (Extract, Transform, Load) processes, dimensional modelling, fact and dimension tables, star and snowflake schemas, OLAP systems, data marts, metadata management, and business intelligence architectures.
The course also emphasizes analytical reporting, dashboard development, KPI monitoring, data storytelling, and strategic decision support using contemporary BI tools such as Power BI, Tableau, SQL-based analytics, and cloud-based data platforms.
In addition, ethical considerations, data governance, data quality, privacy, security, and sustainability principles are integrated into the curriculum to support responsible data-driven decision-making within modern organizations.
Through real-world case studies, laboratory practices, and project-based learning, students will gain the ability to develop scalable business intelligence solutions and communicate actionable insights for business, industrial, and organizational contexts.
Pre-requisites:
Learning Hours Composition:
- 42 hours face to face, consisting of 14 sessions of lecturing, tutorial or workshop.
- 28 hours of Structured Learning and Guided Group Discussions
- 65 hours of Independent, Project-Based Learning
Managing Faculty:
Credit Point:
3 Credit(s)
Learning Hours:
45 hours x 3 CPs = 135 hours
