Data modeling in DBMS (Database Management System) is the process of recording complex software system designs as easy-to-understand diagrams, using symbols and text to represent the way data should flow. The diagram can be used to redesign a legacy application or as a blueprint for creating new software.
Data models are typically created during the analysis and design phase of a project for a complete understanding of the requirements of a new application. Data modeling can be thought of as a flowchart illustrating relationships between data, but capturing all likely relationships in any data model can be time consuming, so this step should not be rushed. Well-documented logical, physical, and conceptual data models allow modelers to catch bugs and make modifications before any programming code is written.
Data modelers regularly use multiple models to view the same data and ensure that all entities, processes, data flows, and relationships have been identified. Various approaches to data modeling include:
me. Conceptual data modeling – Identifies the highest level relationships between two or more different entities.
ii. Enterprise Data Modeling – Similar to Conceptual Data Modeling. However, it addresses the distinctive needs of a particular business.
iii. Logical Data Modeling – Illustrates the specific attributes, relationships, and entities involved in any business function. It is simply the basis for creating the physical data model.
IV. Physical Data Modeling – Represents the database-specific implementation and application of logical data models.
A database model describes the logical layout of the data. The data model defines the relationships between different pieces of data. These models are typically used in data modeling. They are network model, relational model, hierarchical model, object-oriented model, etc.
In this model, entities are represented in a graph that some entities can be retrieved through numerous paths. The network database model was designed to solve some of the serious problems that were experienced with the hierarchical database model. Fix data redundancy by demonstrating relationships as sets rather than hierarchies. Therefore, the hierarchical model is the subset of the network model. This model supports many to many relationships.
In the relational model, data is organized in two-dimensional tables called relations. The tables/relation are related to each other. This model has been widely adopted and considered a great model for efficient data organization. Today, there is a wide collection of relational database products available ranging from lightweight desktop applications to feature-packed server systems with highly optimized recovery methods. Some of the popular RDBMS (Relational Database Management Systems) include Oracle, Microsoft SQL Server, MySQL, IBM, and Microsoft Access.
In the hierarchical model, each entity has only one parent but can consist of multiple children. The root is at the top of the hierarchy and consists of a single entity. The hierarchical model covers a wide spectrum of concepts. It often refers to many configurations, such as multi-tier models, in which multiple tiers of data or information are related to a larger form. The hierarchical model is comparable to the network model in that it displays a group of records in trees instead of arbitrary graphs.
object oriented model
This model was designed to improve database functionality in object programming languages. Object models allow the extension of the semantics of C++, which are Java and Smalltalk object programming languages. They are typically used to provide full-featured database programming capability while maintaining natural language support.
Types of database models By Marcel Douwe Dekker – Own work, CC BY-SA 3.0, via Wikicommons