A **data model** is an abstract representation of the structure, relationships, and constraints governing [[Data|data]] within a system, application, or organization. Data models define how data elements are organized, how they relate to one another, and the rules that govern their use, serving as a foundational blueprint for the design of [[Database|databases]], [[Software application|software applications]], and [[Information system|information systems]]. They are used by [[Data architect|data architects]], [[Database administrator|database administrators]], and [[Software engineer|software engineers]] to communicate data requirements and guide technical implementation. Data models are typically developed at three levels of abstraction. A **conceptual data model** provides a high-level view of business entities and their relationships, independent of any specific technology, and is used primarily for communication between business and technical stakeholders. A **logical data model** refines the conceptual model by defining entities, attributes, and relationships in greater detail, often incorporating [[Data normalization|normalization]] principles, without specifying how data will be physically stored. A **physical data model** translates the logical model into a technology-specific implementation, specifying [[Table (database)|tables]], [[Column (database)|columns]], [[Data type|data types]], [[Index (database)|indexes]], and [[Referential integrity|referential integrity]] constraints for a particular [[Database management system|database management system]]. Several formal modeling approaches are widely used in practice. The [[Entity–relationship model|entity–relationship (ER) model]], introduced by [[Peter Chen]] in 1976, uses entities, attributes, and relationships to represent data structures and remains a foundational technique. The [[Relational model]], developed by [[Edgar F. Codd]] at [[IBM]] in 1970, organizes data into [[Relation (database)|relations]] and underpins most modern [[Relational database|relational databases]]. Other paradigms include [[Dimensional modeling]], commonly used in [[Data warehouse|data warehousing]] and [[Business intelligence|business intelligence]], and [[Object-oriented data model|object-oriented data models]], which align data structures with [[Object-oriented programming|object-oriented programming]] concepts. More recently, [[Graph database|graph models]] and [[Document-oriented database|document models]] have gained prominence in the context of [[NoSQL]] and [[Big data|big data]] systems.