por Do you know what is the data modeling and what are the differences between data models? What are the differences between a conceptual, logical and physical model?
Data modeling (or data modelingfor its English translation) is the process by which data models are created to be stored in a databasewhether relational database or NoSQL database.
This phenomenon allows generating conceptual representations of the objects stored in a data model and making associations between these objects through established rules, while having substantial differences between data models.
Data Model Goals
Before delving into the differences between data models, or the difference between logical and physical database models, you should know some of the objectives of data modeling, among which are:
Ensure that all objects requested by the database are accurately represented. It is important not to omit data in this type of process, since its deletion can cause the creation of incomplete reports and incorrect results. Data modeling supports the creation of models and establishes the differences between data models. Also helps define entities, attributes, relationships, primary and secondary keys and all the elements that are included in a database. Avoid missing data or data redundancy.
Differences between data models in a DBMS
Now, let’s talk about the difference between logical and physical database model, answering the question: What are the differences between a conceptual, logical and physical model? There are several data models involved in the data modeling that are used to represent the data and how it is stored in the database. This causes a difference between the logical and physical database models, which are:
Conceptual model
In this network model defines what the system will contain. It is generally designed by stakeholders salespeople and data architects. It seeks to organize and define the scope, concepts and business rules.
It is generally called a relational model and has attributes, entities and relationships. At this level we do not have such detailed data about the database, since we are barely working on its real structure. Here you can work with query language or SQL, since this is a database oriented towards the relationships between the different entities.
Logical model
A logical data model is one in which defines how the system should be implemented independently of the DBMS. It is also generally created by stakeholders salespeople and data architects.
Here a little more information is added than in the conceptual model and it seeks to provide a basis to form the physical model as such. However, there is still a somewhat generic modeling structure.
In this model no primary or secondary key is yet defined and it is developed independently of the database management system. At the same time, data attributes will have data types with exact extensions, for example VARCHAR(20).
Physical model
The physical data model is an object-oriented model that describes how the system will be implemented using a specific database management system. It is generally created by database administrators and developers, unlike the previous two models, which did not require any very advanced specialization for its implementation. This is one of the main differences between data models.
The physical data model describes a specific database implementation. Provides an abstract outline of the DB; This occurs due to the amount of metadata it has, which also helps to visualize the structure of the database in more detail.
Another difference between data models is that the physical model defines primary and foreign keys, clear and specific data visualizations, indexes, access profiles and authorizations, among others.
So, you have answered some of the questions we asked at the beginning: Do you know what the data modeling and what are the differences between data models? What are the differences between a conceptual, logical and physical model?
Do you want to know more about this topic?
He data modeling and the differences between data models are a widely discussed topic, but with thousands of subtopics, among which are how we create some models from others or what tools are most suitable for which types of models, depending on the differences between data models. and the use that is going to be given to each of them.
Data models are extremely useful tools when it comes to designing databases, since they help us organize the information we have about the different entities of the company and projects. Thanks to this model, errors can also be detected.
If you want to continue learning more about this topic, we invite you to sign up for our Big Data, Artificial Intelligence & Machine Learning Full Stack Bootcamp. Ask for more information and dare to give your career a boost!