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Data modelling is a process in information technology and database development in which data and its structure are represented in an abstract form. The goal of data modelling is to describe the structure, relationships and properties of data in an organised and understandable way. This facilitates the storage, access and management of data in information systems, especially databases. Data modelling plays a crucial role in the planning, development and implementation of databases and information systems.
There are several types of data models, including:
Conceptual data models: These models describe the structure and relationships between different data entities at an abstract, conceptual level. They help to understand the requirements and business concepts and form the basis for the development of databases.
Logical data models: Logical data models are more detailed than conceptual models and describe the data structures, entities, attributes and relationships in a way that is suitable for implementation in a particular database technology. They are independent of the technical implementation and focus on the data itself.
Physical data models: Physical data models are specific to a particular database technology and describe how data is stored at the physical level in the database. They take into account factors such as storage types, indices and performance aspects.
Data modelling tools, such as entity relationship diagrams (ER diagrams) and Unified Modelling Language (UML), are commonly used to graphically represent and communicate data models. Through data modelling, companies and organisations can create a common foundation for database planning and development, which improves data consistency, integrity and availability.
Data modelling is an important step in software development and database management because it helps clarify requirements, define the data structure and ensure that data can be stored and retrieved efficiently and consistently.