Mindavation > We Deliver > Advanced Data Modelling

Advanced Data Modelling

Course Cost:

contact us for details

Duration & Location

2 days - online and onsite*
*min of 8 for onsite delivery

Development Units



Participants have grasped or have experience with the fundamental concepts of data modelling.


This course is designed for business analysts, application developers/analysts, project leaders and data/database administrators


This course extends participants knowledge of data modelling by exploring advanced concepts such as sub-types, recursive and network relationships, denormalization and when to apply it, and other considerations for transforming a logical model into a physical design. It picks up where our introductory course on Data Modelling leaves off. It assumes participants have grasped or have experience with the fundamental concepts of data modelling and builds on them. Depending on the level of experience and knowledge of the participants, this course can be reduced to a 1-day class (by eliminating the sub-types/super-types and recursive relationships sections of the course).

Knowledge Areas Covered

PMBOK Knowledge Areas

Project Stakeholder Management | Project Scope Management | Project Quality Management

BABOK Knowledge Areas

Requirements Analysis and Design Definition

Key Learning Objectives

  • normalize entities to fifth normal form
  • handle complex relationships
    • sub-types and super-types
    • recursive hierarchies
    • recursive networks
  • apply various data modelling guidelines to improve the quality of data models, and therefore the data requirements of an enterprise
  • refine a data model in order to best prepare it for physical database design
  • describe the issues involved with denormalization and explain 2-3 strategies for deciding on; if, when and how to accomplish it. This skill will be useful to work with data analysts and database administrators
  • use two practical methods to balance your data model with processes or use cases, to ensure that all needed data and only needed data is present
  • use State Transition Diagrams to uncover missing data and processes