System Concepts for Data Modeling
System Concepts for Data Modeling
Crystal M. Reedus
CIS 210
November 21, 2010
Abstract Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. Data models support data and computer systems by providing the definition and format of data. From a modeling perspective, the entire problem domain is viewed as a collection of class hierarchies (of objects) that are connected by messages.
Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. Data modeling may be performed during various types of projects and in multiple phases of projects. Data models are progressive; there is no such thing as the final data model for a business or application. Instead a data model should be considered a living document that will change in response to a changing business.
In this paper the focus will be on next generation systems, objected oriented systems and reversed engineered data models. The concept of a data model is really the design for that specific use. Since not every system uses data models the same then there is just a general bases for the system concepts of the data models.
Data models support data and computer systems by providing the definition and format of data. If this is done consistently across systems then compatibility of data can be achieved. If the same data structures are used to store and access data then different applications can share data. The results of this are indicated above. However, systems and interfaces often cost more than they should, to build, operate, and maintain. They may also constrain the business rather than support it. Data models for different systems are arbitrarily different. The result of this is that complex interfaces are required between systems that share data. These interfaces can account for between 25-70% of the cost of current
Crystal M. Reedus
CIS 210
November 21, 2010
Abstract Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. Data models support data and computer systems by providing the definition and format of data. From a modeling perspective, the entire problem domain is viewed as a collection of class hierarchies (of objects) that are connected by messages.
Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. Data modeling may be performed during various types of projects and in multiple phases of projects. Data models are progressive; there is no such thing as the final data model for a business or application. Instead a data model should be considered a living document that will change in response to a changing business.
In this paper the focus will be on next generation systems, objected oriented systems and reversed engineered data models. The concept of a data model is really the design for that specific use. Since not every system uses data models the same then there is just a general bases for the system concepts of the data models.
Data models support data and computer systems by providing the definition and format of data. If this is done consistently across systems then compatibility of data can be achieved. If the same data structures are used to store and access data then different applications can share data. The results of this are indicated above. However, systems and interfaces often cost more than they should, to build, operate, and maintain. They may also constrain the business rather than support it. Data models for different systems are arbitrarily different. The result of this is that complex interfaces are required between systems that share data. These interfaces can account for between 25-70% of the cost of current