New Features
Multiple OIDC Providers per Organization (Beta)
We are adding a new feature that allows you to set up specific OIDC providers for your organization. Whether your company uses multiple identity providers or your tenants prefer to use their own, this feature offers the flexibility to support them. See Multiple OIDCs.
Please note that this is a beta feature currently in early development, so its functionality is limited at this stage.
Rollup Totals
We are introducing a new type of total that aligns with the metric it aggregates. For example, if the metric is SUM, the rollup will also use SUM, and so on.
Rollup totals are “smart” aggregations. They are particularly useful for tables displaying metrics that represent average values, helping to avoid aggregations like averages of averages.
For example:
- For the Won metric, the rollup represents the sum of all regions' won amounts, making the Sum and Rollup (Total) equal.
- For the Avg. Won metric, instead of averaging the row’s values (which are already averages), the rollup averages the original underlying data before it was aggregated by the Won metric and divided into regions like East Coast and West Coast. Consequently, the value of Avg (an average of averages) differs from the Rollup (Total) average (an average based on the original data).
Learn More:
Disable Passing Filters in Drill-Throughs
You can now choose to exclude certain dates or attributes from being applied as filters when drilling into visualizations, dashboards, or drill-downs. This allows for more flexible data exploration by controlling which filters are passed during drills. See Disable Passing Filters in Drill-Throughs for more details.
Upcoming Change
Improved Attribute Filters
We are updating how attribute filters handle values with non-unique secondary labels, such as users sharing the same User Name.
Current Behavior:
When an attribute (e.g., User) has a unique primary label (e.g., User ID: 1234) and a more readable secondary label (e.g., User Name: John Doe), filtering by the User Name (if multiple users are named John Doe) results in all John Does being combined into a single filter value.
New Behavior:
The improved filter will display each attribute value even if the secondary label is not unique. This means you will see all instances of John Doe separately, with a tooltip showing the primary label (e.g., User ID) to help differentiate them. The filter's behavior will be consistent across dashboards, visualizations, and drilling or exploring further interactions, regardless of which label is displayed.
This change is straightforward for end users. However, there will be a new 'Display as' parameter in the metadata to indicate which label should represent the attribute in the GUI. This parameter must be considered when using filters in dashboards, visualizations, drilling, POST messages and events, SDK filter definitions, and cross-filtering.
We do not expect any changes to existing dashboards will be needed. The selection of text from the secondary label will be automatically transformed into a selection of individual attribute values with the value of the secondary label.
More details will be provided in upcoming release notes.