Data Modelling Techniques

A data model is a specification of data structures and business rules. It creates a visual representation of data and illustrates how different data elements are related to each other. Different techniques are employed depending on the complexity of the data and the goals. Below you can find a list with the most common data modelling techniques:

• Entity-relationship modeling. It's one of the most common techniques used to represent data. It's based on three elements: Entities (objects or things within the system), relationships (how these entities interact with each other), and attributes (properties of the entities).
• Dimensional modeling. Dimensional modeling is widely used in data warehousing and analytics, where data is often represented in terms of facts and dimensions. This technique simplifies complex data by organizing it into a star or snowflake schema.
• Object-oriented modeling. Object-oriented modeling is used to represent complex systems, where data and the functions that operate on it are encapsulated as objects. This technique is preferred for modeling applications with complex, interrelated data and behaviors
• NoSQL modeling. NoSQL modeling techniques are designed for flexible, schema-less databases. These approaches are often used when data structures are less rigid or evolve over time

Visit the following resources to learn more:

• @article@7 data modeling techniques and concepts for business
• @article@@articleData Modeling Explained: Techniques, Examples, and Best Practices