Relational Data Design (RDD)

Relational Data Design (RDD) explores how to create an entity-relationship (ER) model of a business function. This seminar is a comprehensive introductory level course, and is an excellent vehicle for introducing the relational database world to I/S professionals.

WHO SHOULD ATTEND

The Relational Data Design course is designed for individuals responsible for data analysis, data modeling, database design, and database implementation - and the administration of a Client-Server database application.

PREREQUISITES

Prior to enrolling in Relational Data Design, students should have a basic working knowledge of the Client/Server environment. For more information, refer to the Introduction To Client/Server Computing seminar outline.

SEMINAR LENGTH

1 days

SEMINAR OUTLINE

1. Overview of Relational Data Modeling

A. The relational data model
B. Modeling complex business data
C. Online Transaction Processing (OLTP) vs Decision Support Systems (DSS)

2. Relationship Concepts

A. Basic terms and concepts
B. Entities
C. Attributes
D. Relationships
E. Tables
F. Codd's 12 Rules
G. Entity-relationship diagrams

3. Normalization

A. The role of normalization in data design
B. First normal form
C. Second normal form
D. Third normal form
E. Denormalizing for performance
F. Handling derived attributes

4. Entity-Relationship Notation and Diagramming

A. Entity-relationship notation
B. Standards and Guidelines
C. Information Engineering
D. IDEF1X

5. Entity-Relationship Modeling

A. Entity-relationship modeling process
B. Identify and gather business information
C. Identify user views
D. Entity-relationship modeling example
E. Integrate user views
F. Decomposition of complex relationships

6. Complete the Relational Model

A. Determine key generation method
B. Data integrity rules

7. Preparation for Database Implementation

A. Stored Procedures and Triggers
B. Cursors: Client and Server Based
C. Identify final characteristics of attributes
D. Preparing materials for physical implementation
E. CASE tools for data design