a collection of concepts that
can be used to describe the structure of a database is a data model.

main categories of data model are:categorize according to the types of concepts they use to describe the database structure. 

High-level or conceptual data models :concepts such as entities, attributes, and relationships.An entity represents a real-world object or concept, such as an employee or a project  that is described in the database. An attribute represents some property of an entity, such as the employee’s name  or  salary.Arelationship among two or more entities represents an association among the entities, for example, a works-on relationship between an employee and a project. 

low-level or physical data models:concepts that describe the details of how data is stored on the computer storage media. Concepts provided by physical data models are generally meant for computer specialists, not for end users.To overcome this problem we use representational data models.These are easily understood by end users but that are not too far removed from the way data is organized in computer storage. Representational data models hide many details of data storage on disk but can be implemented on a computer system directly.Representational data models represent data by using record structures and hence are .sometimes called record-based data models.
We can regard the object data model as an example of a new family of higher-level.

Physical data models describe how data is stored as files in the computer by representing information such as record formats, record orderings, and access paths. An access path is a  search for particular database records efficient, such as indexing or hashing.  An index is an example of an access path that allows direct access to data using an index term or a keyword. 

Another class of data models is known as self-describing data models. The data storage in systems based on these models combines the description of the data with the data values themselves. In traditional DBMSs, the description (schema) is separated from the data. These models include XML as well as many of the key-value stores and NOSQL systems that were recently created for managing big data.