We provide example schemas here, the purpose of these example schemas is multifold.
Definition and Structure: Schemas acts as blueprints for the customer master data, defining the structure and attributes that data entries should follow. This helps ensure consistency and clarity in data management.
Automation and Validation: The schemas are also integral to driving automation processes, validating data entries, and guiding user interactions with the platform. By establishing clear schema field definitions, Pretectum can streamline data entry and reduce errors.
API and Reporting: These schemas also inform the design of APIs and reporting tools, enabling better integration and data retrieval methods. This makes it easier for users to interact with the platform and extract meaningful insights from their data.
Customization: Users can create schemas with various field attributes tailored to their specific needs, allowing for flexibility and adaptability in how data is organized and utilized.
Note the limitations associated with each and every example and consider what is optimal for your organizational context