The Edit View is a central user interface in DataEngine that allows users to create or edit individual records within a module. In this article, we will delve into the Edit View, its functions, and application possibilities in detail.
Creating and Editing Records
The Edit View is where users can create new records within a module. They can also edit and update existing records. This provides an easy way to manage data and ensure that it is always up-to-date.
An important aspect of the Edit View is the ability to specify which fields can be edited. This configuration is typically done by the instance administrator, allowing the user interface to be tailored to the specific requirements of your organization. Only the relevant fields are displayed to optimize the user experience and avoid unnecessary data fields.
Quick Create via SubPanel
In some cases, it is necessary to create records quickly and efficiently without opening the full Edit View. This is where Quick Create via SubPanel comes into play. This feature allows users to create new records directly from a SubPanel, without opening the main editing screen. This is especially helpful when rapid data entry is required.
Integration of Workflows
Workflows are a powerful tool to enhance the Edit View. With workflows, users can supplement additional fields, establish links to other modules, and even create lookup fields based on field values. This enables the automatic completion and linking of records, increasing efficiency and improving data quality.
Synchronization with Other Systems
Through the integration of the HubEngine, data created or edited in the Edit View can be synchronized with other systems. This is particularly useful when real-time information exchange is needed between different applications or platforms. The HubEngine facilitates seamless integration and data transfer.
The Edit View in DataEngine offers a user-friendly way to create and edit records. With configurable fields, Quick Create via SubPanel, workflows, and synchronization capabilities, users can make data management more efficient and effective. This helps streamline workflows and ensure data quality.