Database design is a critical component in the application development process, not just for correctness, but also for performance and scalability. This course focuses on providing a detailed knowledge of how to build data models and includes a discussion on building a statistical data model, as well as describing some of the differences when developing a data warehouse or data mart model.

 Course Description

This course provides participants with a solid understanding of data modeling and its fundamental role in effective system development.

The course begins by providing a solid foundation of the basic terms and concepts. Next, the data model is discussed in detail, covering areas such as how to identify and define entities, identifying business rules which underlie entity relationships, popular notation conventions, considerations in identifying and selecting keys, and subtyping and supertyping of entities. The students perform exercises throughout the course to reinforce the concepts and to draw out questions that arise from practical application of the material.

After exposing the participants to the classical relational data modeling perspective, the course devotes a half-day to an introduction of data warehousing concepts and design. The dimensional data warehouse is contrasted with the relational data model in areas such as purpose of use and performance considerations. Extensive use of examples provides real-life perspectives on the key issues that must be addressed in data warehouse design.

 Audience

This course is intended for application developers, database designers or database administrators.

 Objectives

Participants who have completed this course should be able to undertake data modeling tasks with minimal direction in either the relational or data warehousing arenas with the following topics:

• Basic data-modeling concepts
• Entities
• Attributes
• Relationships
• Cardinality, Optionality
• Integrating ERDs
• Identifying Keys
• Normalization, Denormalization
• Integrity Rules
• Statistical Data Modeling
• Performance Considerations
• Data Warehousing Concepts and Design

 Prerequisites

Relational Database Concepts (DB100) and SQL Programming (DB102) or equivalent background.