The Data Modelling course and lab cover the entire field of how to create data models that allow complex data to be analysed, manipulated, extracted and reported upon accurately. The computer architecture course and lab also provide knowledge on the areas such as I/O functions and structures, RISC, and parallel processors with real-world examples enhancing the text for reader interest.
Lessons 1: Introduction
- Who Should Read This Course
- What the Course Covers
Lessons 2: Introduction to Data Modelling
- Data-Centric Design
- Anatomy of a Data Model
- Importance of Data Modelling
- Measures of a Good Data Model
- How Data Models Fit Into Application Development
- Data Modelling Participants
Lessons 3: Relational Model Components
- Conceptual and Logical Model Components
- Physical Model Components
Lessons 4: Data and Process Modelling
- Data Model Diagramming Alternatives
- Process Models
- Unified Modelling Language (UML)
- Relating Entities and Processes
Lessons 5: Organising Database Project Work
- The Traditional Life Cycle
- Non-traditional Life Cycles
- The Project Triangle
Lessons 6: Conceptual Data Modelling
- The Conceptual Modelling Process
- Creating the Model
- Evaluating the Model
Lessons 7: Logical Database Design Using Normalisation
- The Need for Normalisation
- Applying the Normalisation Process
- Denormalisation
- Practice Problems
Lessons 8: Beyond Third Normal Form
- Advanced Normalisation
- Resolving Supertypes and Subtypes
- Generalising Attributes
- Alternatives for Reference Data
Lessons 9: Physical Database Design
- The Physical Design Process
- Designing Tables
- Integrating Business Rules and Data Integrity
- Adding Indexes for Performance
- Designing Views
Lessons 10: Alternatives for Incorporating Business Rules
- The Anatomy of a Business Rule
- Implementing Business Rules in Data Models
- Limitations on Implementing Business Rules in Data Models
- Functional Classification of Business Rules
Lessons 11: Alternatives for Handling Temporal Data
- Temporal Data Structures
- Calendar Data Structures
- Business Rules for Temporal Data
Lessons 12: Modelling for Analytical Databases
- Data Warehouses
- Data Marts
- Modelling Analytical Data Structures
- Loading Data into Analytical Databases
Lessons 13: Enterprise Data Modelling
- Enterprise Data Management
- The Enterprise Data Model
Hands-on LAB Activities
Introduction to Data Modeling
- Creating a Conceptual model
- Creating a Physical Data Model
- Creating a Logical Data Model
Relational Model Components
- Modifying a Conceptual Model
Data and Process Modelling
- Drawing of a Conceptual Model with Nested Subtypes
Organising Database Project Work
- Discussing the Traditional Life Cycle and Requirements Gathering
- Testing the Knowledge of Project Database Management Tasks
- Discussing Nontraditional Life Cycles and the Project Triangle
Conceptual Data Modeling
- Creating a Conceptual Model for the Employee Management System
Logical Database Design Using Normalisation
- Creating a Data Model in Second Normal Form
- Creating a Data Model in First Normal Form
- Analysing Normalization in Academic Tracking Database
Beyond Third Normal Form
- Creating a Data Model in Fourth Normal Form
- Creating a Complex Logical Data Model
Physical Database Design
- Converting a Logical Data Model into a Physical Data Model
- Creating a Physical Data Model ERD
- Creating a Data Model in Third Normal Form
Alternatives for Incorporating Business Rules
- Modelling Business Rules in a Logical Data Model
Alternatives for Handling Temporal Data
- Adding History to Data Models
Modelling for Analytical Databases
- Designing a Star Schema Fact Table
Enterprise Data Modelling
- Developing an Enterprise Conceptual Model
Standard: