Data Modeling is an established technique of comprehensively documenting an application or software system with the aid of symbols and diagrams. It is an abstract methodology of organizing the numerous data elements and thoroughly highlighting how these elements relate to each other. Representing the data requirements and elements of a database gra phically is called an Entity Relationship Diagram, or ERD.
What is an Entity?
Entities are one of the three essential components of ERDs and represent the tables of the database. An entity is something that depicts only one information concept. For instance, order and customer, although related, are two different concepts, and hence are modeled as two separate entities.
A data model entity typically falls in one of five classes – locations, things. events, roles, and concepts. Examples of entities can be vendors, customers, and products. These entities also have some attributes associated with them, which are some of the details that we would want to track about these entities.
A particular example of an entity is referred to as an instance. Instances form the various rows or records of the table. For instance, if there is a table titled ‘students,’ then a student named William Tell will be a single record of the table.
Why Do We Need a Data Model Entity?
Data is often stored in various forms. An organization may store data in XML files, spreadsheets, reports, and relational databases. Such a fragmented data storage methodology can present challenges during application design and data access. Writing maintainable and efficient code becomes all the more difficult when one has to think about easy data access, scalability, and storage. Additionally, moving data from one form to the other is difficult. This is where the Entity Data Model comes in. Describing the data in the form of relationships and entities, the structure of the data becomes independent of the storage methodology. As the application and data evolve, so does the Data Model Entity. The abstract view allows for a much more streamlined method of transforming or moving data.