Traditional entity-relationship modeling and normalization techniques capture only the structural and static relationships of data. This seminar addresses modeling the behavioral aspects of data to provide robust, high-integrity, resource-centric application development and database design.

You learn how to apply object-oriented concepts to data modeling including inheritance and life cycle state, as well as how to model business rules and integrity policies. How to model time-dependent data and distributed data are addressed.

Data models must support not just applications, but business process re-engineering, TQM processes, as well as rapid application development (RAD) projects. In this seminar you learn how to model generic data types to support flexible design. Accelerated data modeling workshops are required to support RAD projects while increasing consensus definition and stable enterprise data models. Critical to the success of data modeling workshops are techniques for managing group dynamics and team-building.

The real value of data models is when they are translated into flexible and stable databases with resource-centric applications that implement effectively re-designed business processes. This seminar shows you how.

• Identify and model special cases of data, such as:
  • Types and subtypes with inheritance
  • Object-oriented entity life cycles
  • Temporal Data
  • Higher normal forms
  • Business rules and integrity policies
  • Generic data types
  • Non-traditional data types
• Develop distributed data models
• Describe the components of a resource-centric application architecture
• Describe techniques for facilitating rapid data modeling workshops and managing group dynamics
• Describe how to validate the quality of a data model
• List the guidelines for transitioning a data model for physical database design including:
  • How to implement subtype and entity states
  • When to compromise a normalized data model
  • How to implement generic data types

 

5. Modeling Distributed Data

• The Zachman framework for information architecture
• Client/server model framework
• The client/server paradigm and data management
• Distribution analysis
• Client/server design guidelines
• Integrity implementation in the client/server environment

 

6. Value-Centric Information Systems Engineering

• The resource life cycle approach to application development
• Process ownership and information stewardship
• Encapsulated application development

 

7. Accelerated Data Modeling Workshops

• Objectives & tasks
• Facilitation skills
• Techniques for effective workshops and group dynamics

8. Transitioning a Conceptual Data Model for Physical Database Design

• Model simplification principles
• Transaction analysis and logical access maps
• Index identification and data clustering
• Type/subtype implementation
• Entity life cycle implementation
• The information warehouse
• Guidelines for compromising the conceptual model

9. Future Trends in Information Modeling

• Class libraries and template models
• Behavior models
• Intelligent database: The convergence of information technologies