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COURSE Title:
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ADVANCED DATA MODELING:
Objects, Business Rules, and Other Important Things |
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Why This Course?
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The emergence of data warehouse, object technology, multi-media, document, rule-based and other complex data type technology has created a challenge to traditional data modeling methods. Furthermore, the World Wide Web has altered shape of both business work and information management.
Basic entity-relationship modeling and normalization techniques capture only the structural and static relationships of structured data. This seminar addresses semantic modeling of complex information types along with the behavioral aspects of data. This provides robust, high-integrity, value-centric application development and database design and exploitation of today's emerging technologies.
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 more than application development. They support business communication, business reengineering, TQM, Total Information Quality Management (TIQMTM ), and rapid application development (RAD) projects. You learn how to model generic data types to create flexible design that supports rapid business change.
Informational applications such as data warehouse, decision support and executive information systems require models that are inherently different from operational data models. You learn rules and guidelines for effective data warehouse modeling and design to support the strategic and tactical processes of the enterprise.
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Learning Outcomes:
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- Identify and model special cases of data, such as:
- Types and subtypes with inheritance
- Object/entity life cycles and state transition diagrams
- Time-variant data
- Generic data types and metadata types
- Define and model business rules and data integrity policies
- Develop data warehouse data models including star schema models
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Describe and model hypermedia and other complex information types
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Audience:
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Information and resource management staff, DBAs, systems analysts and application developers who participate in data requirements definition, data analysis and data modeling, data warehouse staff, Web-data designers
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Format:
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Lecture with exercises and discussion to reinforce the concepts
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Duration:
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3 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: The emergence of data warehouse, object technology, multi-media, document, rule-based and other complex data type technology has created a challenge to traditional data modeling methods. Furthermore, the World Wide Web has altered shape of both business work and information management.
Basic entity-relationship modeling and normalization techniques capture only the structural and static relationships of structured data. This seminar addresses semantic modeling of complex information types along with the behavioral aspects of data. This provides robust, high-integrity, value-centric application development and database design and exploitation of today's emerging technologies.
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 more than application development. They support business communication, business reengineering, TQM, Total Information Quality Management (TIQMTM ), and rapid application development (RAD) projects. You learn how to model generic data types to create flexible design that supports rapid business change.
Informational applications such as data warehouse, decision support and executive information systems require models that are inherently different from operational data models. You learn rules and guidelines for effective data warehouse modeling and design to support the strategic and tactical processes of the enterprise.
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Advances in Data Modeling Methods
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- The ?why? of data modeling
- Paradigms for data modeling
- Data and the Resource Management Life Cycle
- Semantic network influences
- Classification theory and taxonomy
- Object-oriented analysis and modeling
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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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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
- Dynamic object models and event models
- Object state and state transition in the real world
- Entity life cycles
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Business rules: Modeling Integrity Constraints and Policies
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- Model and taxonomy for business rules
- Business rule definition
- Business rule format
- Business rules as pre-conditions and post-conditions
- Characteristics of effective rules
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Data Warehouse Modeling
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- Data warehouse and business intelligence
- Supporting strategic and tactical business processes
- Identifying data subjects
- Data analysis for data warehouse
- Data warehouse attribute inclusion rules
- Classifying time-variant data
- Star schema modeling
- Determining dimensions
- Summary and derived data modeling
- Rules for de-normalization
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Modeling Hypermedia Data types for Internet and Multi-Media Databases
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- Impact of Internet and Intranet on information management
- Non-traditional information types
- Hypermedia modeling: nodes and links
- Semantic data modeling
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Future Trends in Information Modeling
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- Template models
- Model-driven engineering
- The future of software package data models
- Intelligent database: convergence of information technologies
- Remembering the goals of data modeling
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