Mapping or converting logical data model to physical data model is done typically through normalization. It is not always straightforward that entities get converted to tables.

A logical data model is a more abstract and conceptual view of the data, focusing on the entities, attributes, and relationships without considering the technical aspects of the database system.

Abstract Entity relationship diagram (ERD) is one of the most widely used technique for data modeling. An ERD developed during the conceptual data modeling phase of the database development process is ...

One of the most important steps in desiging a database is establishing the data model. Part one of a two-part article describes how to create a logical model.

A logical model should be normalized (to at least third normal form). This runs contrary to what lots of people say, but remember, normalization does not presuppose the granularity of the data.

A logical entity definition may reference (reuse) other object definitions to better organize or factor a data model. For example, an entity may extend another entity, include entity-typed attributes, ...

In the simplest terms, a logical data model is a visual representation of the business rules and requirements covering the universe-of-discourse for a given solution or enterprise, along with some ...

Over-normalization can result in a loss of semantic details and integrity. Data modeling is a semantic process and as such, it will always remain more art than science. Consider your logical data ...

Inverse modeling is the process uncovering the relationships from the system observations to its inputs. It is essential in various fields such as control, robotics, and signal processing. We propose ...

The data modeling course entails all the important points related to conceptual, logical, and physical approaches. You will learn to draw Entity-Relationship Diagrams (ERDs) and the normalization ...