In computer science, data modeling is the process of structuring and organizing data, typically using a database management system.
Managing large quantities of structured and unstructured data is a primary function of information systems. Data models describe structured data for storage in data management systems such as relational databases. They typically do not describe unstructured data, such as word processing documents, email messages, pictures, digital audio, and video. Early phases of many software development projects emphasize the design of a conceptual data model. Such a design can be detailed into a logical data model. In later stages, this model may be translated into physical data model.
The entities represented by a data model can be the tangible entities, but models that include such concrete entity classes tend to change over time. Robust data models often identify abstractions of such entities. For example, a data model might include an entity class called "Person", representing all the people who interact with an organization. Such an abstract entity class is typically more appropriate than ones called "Vendor" or "Employee", which identify specific roles played by those people.
A proper conceptual data model describes an organization's semantics. It is a collection of assertions about the nature of the organization. Proper entity classes are named with natural language words instead of technical jargon. Likewise, properly named relationships form concrete assertions about the organization. For example, a relationship called "is composed of" operating on entity classes "Order" and "Line item" forms the concrete assertion "Each Order is composed of one or more Line items."
While data analysis is a common term for data modeling, the activity actually has more in common with the ideas and methods of synthesis (inferring general concepts from particular instances) than it does with analysis (identifying component concepts from more general ones). {Presumably we call ourselves systems analysts because no one can say systems synthesists.} Data modeling strives to bring the data structures of interest together into a cohesive, inseparable, whole by eliminating unnecessary data redundancies and by relating data structures with relationships.
A different approach is through the use of adaptive systems such as artificial neural networks that can autonomously create implicit models of data.
This article is licensed under the GNU Free Documentation License.
It uses material from the
"Data modeling".
Home Page • arts • business • computers • games • health • hospitals • home • kids & teens • news • physicians • recreation• reference • regional • science • shopping • society • sports • world