Recommendations for Custom Dashboards
This guide provides recommendations for creating and using custom dashboards. It includes basic instructions to help you customize and manage dashboard components effectively.
The following are the recommendations:
Maximum number of datasets that can be blended in a dashboard: Digital.ai recommends using maximum six datasets in a dashboard. Dashboard performance depends on several factors including the size of the datasets, the number of objects, rows, and cache size. As the number of datasets increases, performance may deteriorate because the server creates a virtual dataset by joining all datasets included in the dashboard. Therefore, the more datasets you add, the longer it may take for the dashboard to execute.
All the datasets being used are linked and form a virtual dataset for the faster analysis of the dashboard.
Maximum number of chapters and pages allowed in a dashboard: It is recommended for each dashboard to have a maximum of 2 chapters and no more than 5 pages in total across all chapters.
Basic instructions for creating a derived metric: Derived metrics and derived attributes are calculated dynamically during dashboard execution. The calculation time can vary based on the size and complexity of the data, and may occasionally take several seconds. To ensure optimal performance, create derived metrics according to clear business definitions and regularly remove any unused derived metrics or attributes.
Maximum number of derived metrics that can be created in a dashboard: Consider creating derived metrics based on business definition requirements and routinely removing any unnecessary objects. The suggested maximum number of derived metrics per dashboard is 50.
By following these recommendations, you can create and maintain custom dashboard efficiently. Regularly reviewing and optimizing your dashboard components will help ensure good performance and allow your dashboards to adapt to changing business requirements.