What is Conceptual Data Model?
A conceptual data model is the most abstract data model or the summary level data model. Platform-specific information and other implementation information such as interface definitions or procedures are eliminated in this data model. A conceptual data model is useful because of its simplicity. It is often used for communicating ideas and in strategic data projects.
A conceptual data model is also known as a conceptual schema.
A conceptual data model provides extensive coverage of business concepts and is primarily designed for a business audience. It is never a solution model and is technology and application neutral. In other words, the conceptual data model is a business model from a data point of view. The business uses the conceptual data model for confirmation and correction. Because these are high-level models, attributes are typically not added to conceptual data models. They help in establishing relationships between entities, but may not provide the properties 'null' and 'cardinality'. Conceptual data models are often designed to be independent of data storage technologies or database management systems (DBMS). Conceptual data models are often created as part of the initial requirements effort. These models help to explore high-level concepts and static business structures. Traditional teams use conceptual data models as precursors or alternatives to logical data models (LDMs).
A conceptual data model helps identify key business and system units at a high level and build the relationships that exist between them. It also helps in defining the main problems out of problems to be addressed by the system. It can address both digital and non-digital concepts. A conceptual data model can also help bridge the gaps between a solution model and a requirements document.