Mendix has established itself as a leader in the low-code development world thanks to its state-of-the-art features that simplify application development. This low-code platform integrates advanced tools and technologies to help you build enterprise-grade apps and components faster and more efficiently. For instance, Mendix Solutions allows you to easily create custom data models faster and more effectively with minimal effort. However, like any other platform, you should follow several best practices to optimize the process of creating custom models and the outcome.
If you’re new to the Mendix, worry not – here are some best practices for creating custom data models in Mendix and examples you should know about.
Mendix Best Practices for Creating Custom Data Models
1. Plan and Design
While it may be easy to create custom data models in Mendix, prior planning and designing are crucial. It helps you understand the application’s requirements and determine the necessary data entities, their relationships, and the properties they should have. To effectively plan your custom data models, do the following:
· Identify Entities
Start by defining what entities should be modeled. An entity is a real-world concept or object with a unique identity, attributes, and relationship with different entities. For instance, when modeling a sales application, the entities involved may include products, salespersons, customers, and orders.
· Define Attributes
What attributes do your entities have? Attributes are features that define your entities. For instance, a product (as an entity) may have attributes such as name, SKU, and price.
· Determine Relationships
How do entities relate to one another? Relationships help you link the identified entities with one another. For instance, a customer may place multiple orders, but a specific order is only placed by a single customer.
Developing and designing a plan ensures that you build a custom data model that matches your application’s needs and is scalable to accommodate future changes. Also, it prevents you from creating too complex or difficult-to-understand custom data models. Therefore, you should take your time to fully understand your app’s requirements and craft a comprehensive plan before building a custom data model. Doing so will save time and prevent avoidable issues down the line.
2. Use Mendix’s Common Naming Conventions
Mendix has documented a comprehensive guideline for adopting consistent modeling and naming conventions when building Mendix apps and components. It requires you to use standard naming conventions for attribute and entity names and enumeration values. This helps maintain consistency and makes it easier for others to understand, use, and improve custom models.
Even with the robust search and navigation support in Mendix Studio Pro, it is crucial to adhere to the common naming conventions because:
- A named and structured custom data model helps others identify reusable code
- Anyone should quickly understand an existing application or custom data model, including where it is located and how its different parts are connected
- Once you finish creating a custom data model for your application, it’s handed over to others for maintenance. Therefore, even years later, they’ll need to understand and decipher what you did and how they can improve it.
3. Use Inheritance
Using inheritance to build a hierarchical structure for your custom data model enables you to reuse associations and attributes across entities. This approach makes it easier to manage and extend your data models.
Also, inheritance allows you to add new entities quickly because you can inherit all attributes and associations from the existing entities. What’s more, using inheritance makes your custom data model more efficient and flexible, as it reduces the need for duplicate associations and attributes.
4. Define Validations and Constraints
Defining validations and constraints when creating a custom data model in Mendix is crucial. Validations ensure that the data entered into the application data model is consistent and accurate. On the other hand, constraints ensure the data stored in the data model meets specific requirements, including setting maximum and minimum values, mandatory fields, and data type restrictions.
Defining validations and constraints for your data model improves the overall data quality and prevents inconsistencies and errors. Therefore, the custom data models will work as expected, saving time and potentially costly mistakes in the long run.
5. Keep it Simple
As initially stated, custom data models will be used by other developers once it is published on the Mendix Marketplace. Creating a complex custom data model implies that it would be difficult for others to understand and improve your data model in the future. Therefore, you should avoid creating too many attributes or entities to ease future improvement and enable others to understand your data model faster.
6. Regularly Test and Validate Your Data Model
Mendix supports agile development, which promotes continuous improvement. Therefore, creating your data model is just the beginning of a continuous improvement process. Test and validate your application data model regularly to ensure it works as expected and meets your application’s requirements. Doing ensure consistency and prevents potentially costly errors caused by a faulty data model.
Examples of Custom Data Models in Mendix
There are many examples of custom data models you can create with Mendix. Some of them include the following:
1. Sales Custom Data Model
A sales data model might have several entities, such as products, orders, and customers. The customer entity may have attributes like name, phone number, address, and email. The relationships between different entities, like the customer-to-order relationship, may be one-to-many, whereas order and product entities may have a many-to-many relationship.
2. E-commerce Data Model
This custom data model may include payments, orders, customers, and products as entities. Such a data model enables businesses to manage online stores and process customer orders.
3. Human Resource Management Data Model
This custom data model may feature several entities, including employees, performance evaluations, departments, and positions. The employee entity may have attributes like name, phone number, role, and ID in this case. The relationship between two entities, employee and position, may be one-to-one. Having such a custom data model helps you manage employees and monitor their performance effectively.
Final Thoughts
Mendix allows you to quickly create custom data models. While it may seem easy to create custom data models in Mendix, you must follow the discussed best practices to get the best outcome. Building data models following these practices enables you to create models that meet your application’s requirements perfectly.
Interested in creating custom data models faster? Visit the Mendix platform to build these data models the easy way.
