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Introduction to Modeling for Data and Process
A One-day Experiential Workshop
Abstract
As more and more businesses realize that information is at the heart of their core competency and key to maintaining their competitive edge, they struggle with a standard way to represent this key corporate asset. Often, the business managers, who are the makers of the business rules, are thwarted in their quest for meaningful information by archaic systems with unorganized data definitions. Business process re-engineering efforts are often separate from and have difficulty connecting to the data management efforts of the enterprise. What's the best way to model the key processes and data of the company? All this modeling 'takes too long' and 'can't really be implemented'.
This course is designed to familiarize business and IS professionals with the fundamental principles, concepts, and standards of data and process modeling. The attendees will learn the elements of modeling via participatory presentation, discussion, and exercises from real-world situations.
Audience
The introductory course is designed for business and information systems analysts, data administrators, project leaders, and consultants who are responsible for defining and documenting the data and process rules for the business. Course size is limited to 16 attendees. A minimum of six attendees is recommended. Prior attendance at the one-day Data Management Concepts course is strongly recommended.
Course Outline
- 1. Review of Data Management Concepts, or 'Why Bother with Modeling?
- The Objectives of Modeling
- 2. Designing for Integration: 'All models are wrong, but 'good' one's are useful
- 3. Data Modeling Fundamentals
- Bottom Up, or Top Down? Levels?
- Barriers and Enablers
- Definitions
- The Elements of Data Modeling
- Notation: A picture of the business rules
- Rules for producing a 'good' model
- The ABC Library
- 4. Process Modeling Fundamentals
- Definitions
- The Elements of Process Modeling
- Notation: A picture of the business processes
- Interconnection with Data Modeling
- How many levels of decomposition?
- The ABC Library
- 5. Verification of Models
- Process and Personnel
- Checking for Quality and Completeness
- 6. Implementation of Models
- Turning Business Rules into Information Systems
- The Connection: Conceptual, Logical, and Physical Models
- Relationship to the Software LifeCycle
- The use of CASE tools
- 7. Wrap-up and Conclusion
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