Advanced Data Modelling

Basic knowledge of relational databases, schema design, and SQL. Familiarity with data warehousing concepts, NoSQL, and big data processing is recommended.

Course: ICAT2170 Databases, ICAT2180 Database Programming and ICAT 3320 Advanced Data Architecture

This course provides an in-depth exploration of advanced data modeling techniques, covering relational, dimensional, NoSQL, and big data models. It focuses on designing scalable, efficient, and purpose-driven data models for modern data architectures. By the end of this course, students will be able to analyze and refine data models using Entity-Relationship (ER) diagrams, UML modeling, and data vault techniques, understand different schema designs, including star schema, snowflake schema, and hybrid approaches, understand, design and implement graph database models, develop NoSQL data models for document and wide-column stores, integrate spatial and temporal modeling for location-aware and time-series data, use industry-standard modeling tools, critically evaluate data models for performance, scalability, and maintainability.

• Data Modeling Essentials – Graeme Simsion & Graham Witt (Relational & Dimensional Modelling)
• Graph Databases: New Opportunities for Connected Data – Ian Robinson et al.
• Lecture slides, scientific papers and related books
• Other materials provided during the course.

The course will be offered for the first time in the academic year 2026-2027.