Physical data model: properly structure your data base
The physical data model (MPD) is a decisive step in the design and management of a database.
Unlike the conceptual or logical data model, the physical model focuses on how data will actually be stored and manipulated by a database management system (DBMS).
In this article, we'll explore what an MPD is, why it's essential in managing information, and how to create one effectively, while also emphasizing the importance of a MDM (Master Data Management) to centralize and manage data.
What is a physical data model?
A physical data model (MPD) is the concrete translation of the logical data model into a technical database structure (DBMS).
It includes all the details needed to implement the model in a specific DBMS, such as tables, columns, data types, indexes, primary and foreign keys.
It is used to describe how data will be stored, retrieved, and managed in a database.
Example:
If the logical data model defines entities as a product, category, and order, the physical model will detail the structure of each table, specifying details such as data types (varchar, integer), column lengths (e.g. product name - 255 characters), and constraints (primary key, foreign key).
Why is the physical data model important?
1. Optimizing database performance
The MPD makes it possible to optimize the structure of the database so that it effectively meets the needs of users and applications. By choosing the good data types, the indexes, and by optimizing relationships, the performance of the database is improved.
2. Translating the logic model into a technical structure
The model data logic (MLD) provides an overview of entities and relationships, but does not include technical implementation.
The physical model details this structure so that it can be directly used in a DBMS, thus ensuring that business requirements are well translated into technical constraints.
3. Data consistency thanks to keys and constraints
Through the addition of primary keys, foreign keys, and other constraints, the MPD ensures data consistency, avoiding duplicates or inconsistencies in stored information. The MDM (Master Data Management) can then reinforce this coherence by centralizing the data.
The components of a physical data model
The main components of an MPD include:
1. Tables
Les tables Are the basic structures where the data is stored. Each table generally corresponds to an entity defined in the logical model (for example, product, customer, order).
2. Columns and data types
Each table has columns that represent the attributes of the entity. The MPD specifies the data types (texts, numbers, dates) and their sizes to optimize storage and performance.
3. Primary and foreign keys
- Primary key (PK) : A unique identifier for each record in a table (e.g. product ID).
- Foreign key (FK) : Link between two tables to establish a relationship (e.g. category ID in the product table).
4. Constraints and indexes
Les stresses (uniqueness, non-zero values) ensure the validity of the data, while the indexes improve search speed in the tables.
5 steps to create a physical data model
- Choosing the DBMS
Choose a database management system (MySQL, PostgreSQL, Oracle, etc.) that meets your business needs. Each DBMS has its own specificities and functionalities.
- Translating the logic model into tables
Convert each entity in the logical model into a table, and define the appropriate columns and data types for each attribute.
- Define relationships between tables
Add foreign keys to establish relationships (one-to-one, one-to-many) defined in the logic model.
- Optimize the model
Use indexes to speed up searches, add constraints to ensure data integrity, and adjust data types to optimize database size.
- Validate and test the physical model
Before moving on to implementation, validate the model with stakeholders and conduct performance testing to ensure that the model is effective.
Example schema for a physical data model
An MPD schema is often represented as a entity-relationship diagram (DER), but with a much more technical level of detail.
Here is a simplified example:
Main tables:
- Product: Product ID (PK), name, price, price, stock, category ID (FK)
- Category: category ID (PK), category name
- Customer: customer ID (PK), name, email, address
- Order: Order ID (PK), date, total, customer ID (FK)
Relationships between tables:
- A product is linked to a category by the foreign key Category ID.
- An order is linked to a customer by the foreign key Customer ID.
- An order may contain multiple products, which may require an additional “Order Details” table to manage these relationships.
Tools for creating and managing a physical data model
- MySQL Workbench : A popular tool for designing physical models, and managing MySQL databases.
- pgAdmin : Designed for PostgreSQL, it allows you to create and manage physical data models.
- Erwin Data Modeler : A more advanced tool for modeling physical data, compatible with several DBMS.
For a global management of your product information And a perfect consistency of your data on all channels, an MDM like the one offered by SolidPepper is an excellent complement to the physical model. It centralizes data and guarantees optimal quality of information on all sales channels.
Conclusion
The physical data model is a central element in the design of any database. By transforming the logic model into a technical structure, it ensures that data is stored in a consistent, optimized, and accessible manner.
Whether you manage a large product catalog or complex customer information, building your MPD well ensures better database performance and effective data management.
Try it for free for 30 days, SolidPepper solutions and start to streamline the management of your product data.
FAQS
What is the difference between a logical model and a physical data model?
The logical model is an abstraction of data without considering technical constraints, while the physical model describes how that data is stored in a database.
What are the main elements of a physical data model?
Key elements are tables, columns and their data types, primary and foreign keys, and constraints and indexes.
How to optimize a physical data model?
Optimization involves choosing the right types of data, adding indexes for quick searches, and constraints to ensure data integrity.
Why is MDM important in data management?
MDM makes it possible to centralize and manage all data in a coherent manner, thus facilitating the management of the physical data model and guaranteeing optimal data quality.
What tools should you use to create a physical data model?
Tools like MySQL Workbench, pgAdmin, or Erwin Data Modeler are ideal for designing and managing physical data models.
