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COURSE Title:
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ADVANCED DATA MODELING AND VALUE-CENTRIC APPLICATION DEVELOPMENT |
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Why This Course?
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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, value-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 value-centric applications that implement effectively re-designed business processes. This seminar shows you how.
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Learning Outcomes:
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Upon completion of this seminar, you will be able to:
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Identify and model special cases of data, such as:
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Develop distributed data models
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Describe the components of a value-centric application architecture
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Describe techniques for facilitating rapid data modeling workshops and managing group dynamics
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Describe how to validate the quality of a data model
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List the guidelines for transitioning a data model for physical database design including:
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Audience:
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Data administrators, data and information resource management staff, DBAs, systems analysts and application developers who participate in data requirements definition, data analysis and data modeling
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Format:
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Lecture with numerous exercises and a case study
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Duration:
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3-4 Days
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Pre-requisites:
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Basic data modeling training with a minimum of six months data modeling experience
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Abstract:
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ABSTRACT: 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, value-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 value-centric applications that implement effectively re-designed business processes. This seminar shows you how.
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Modeling Generic Entity Types
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- Meta data as data
- Relationship types
- Data model patterns
- Generic data models and flexibility design
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Advances in Data Modeling Methods: Paradigms for Information Management
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- The ?why? of data modeling
- Paradigms for data modeling
- The business value chain
- Data and the Resource Management Life Cycle
- Semantic network influences
- Classification theory and taxonomy
- Object-oriented analysis and modeling
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Object Concepts Applied to Data Modeling
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- Object class as an extension of entity type
- Abstraction and encapsulation
- Object typing and inheritance
- Entity types and subtypes
- Object behavior and event modeling
- Object state and state transition
- Entity life cycles
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Modeling Distributed Data
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- The Zachman framework for information architecture
- The client/server paradigm and information management
- Distribution analysis
- Integrity implementation in the client/server environment
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Value-centric Information Systems Engineering
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- The resource life cycle approach to application development
- Application design for common processes and local extensions
- Process ownership and information stewardship
- Encapsulated application development
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Accelerated Data Modeling Workshops
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- Objectives & tasks
- Facilitation skills
- Techniques for effective workshops and group dynamics
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Transitioning a Conceptual Data Model for Physical Database Design
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- Model simplification principles
- Transaction analysis and logical access maps
- Index identification and data clustering
- Type/subtype implementation
- Entity life cycle (object state) implementation
- Guidelines for compromising the conceptual model
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Future Trends in Information Modeling
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- Class libraries and template models
- Behavior models
- Intelligent database: The convergence of information technologies
- Remembering the goals of data modeling
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