1

Introduction

• The role of data in the IS.
• Overview of modeling techniques and methods.

2

Data Dictionary

• Data search.
• Sources: Review of existing applications, management documents, strategic choices of the company.
• Data description: Naming rules, definition rules. Documenting existing systems.

3

Semantic data modeling

• How to define data independently of the logical and physical infrastructure.
• Data modeling levels: Specification level; design specification level.
• Approaching this problem with UML. The UML class diagram. Classes, attributes, objects, associations, constraints.
• How can the same problem be handled with another formalism? The entity-relationship diagram.
• Standardization. How do normal forms help to understand the data?
• The role of data in the description of business and oversight processes.
• Get users involved in data modeling. Validation.
• Addressing data in the context of detailed specification validation.

4

Logical data modeling

• The stages of model transformation.
• The rules for moving from a semantic (conceptual) model to a logical model.
• The passage from a logical model to the physical model, the optimization work.
• Project manager’s participation in the optimization work.

5

Modeling tools

• Presentation of a UML tool (StarUML and/or PowerAMC).
• Presentation of an entity-relationship tool (PowerDesigner "MCD version").