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Using dashboard filters
Using dashboard filters
Tom Azernour avatar
Written by Tom Azernour
Updated over a week ago

Filtering allows you to refine your dashboard’s insights and drill down to focus on a specific subset of data.

Dashboard filters are a good way to simplify the configuration of insights, eliminating the need to repeatedly apply the same filters on each insight inside a dashboard.

Dashboard filters are easy to use, which makes them particularly suitable when sharing a dashboard with team members or stakeholders who are less proficient with the Keypup platform.

Dashboard filters are commonly used to filter on:

  • A date range (reporting range)

  • A specific user or list of users (team-level filtering)

  • A specific project (project-level drill down)

  • A list of labels (feature vs bug segmentation)

Where to find and configure dashboard filters?

Once enabled, dashboard filters appear at the top of your dashboard, just above your insights.

All dashboard templates are pre-configured with filters. You can edit the value of each filter by clicking them.

If you see no filters, it means none have been created for this dashboard. See our next section to learn how to add filters to your dashboard.

Create and apply dashboard filters

Dashboard filters can be created by any user that has Owner or Editor permissions on a dashboard.

To add a new filter, click on the New filter button at the top right of your dashboard. This will open the dashboard configuration window.

The following must be completed to create a filter:

  • Filter name: the name that will show on the dashboard as an indication.

  • Type: the type of input. A filter can only apply to fields having the same type (e.g. date filter can be applied to an insight on created_at, to another insight on merged_at but cannot be applied to an insight author field) The following types are available

    • Date or time range

    • Number

    • Text only

    • Text/Text list

    • Single user

    • Single/Multi user

  • Link between filter and dashboard insights (Optional): specify how your filter will apply to each insight on your dashboard. By default, new filters will not apply to any insight until you select a field (which replaces "None" in the dropdown). Read more here and see examples here).

  • Value: the filtering value that will be applied on each insight (e.g. “reporting range is current quarter”, “user is John Doe”, “labels are Bug, Documentation”).

Once completed (see configuration examples below), click Create filter on the bottom right of the window to save it to your dashboard.

You will be redirected to the dashboard in edit mode. Click Save to save the dashboard and filters in the current configuration.

Quickly edit dashboard filters values

You can quickly edit a filter value by clicking your filter’s button.

The changes will be immediately visible on your insight, but will not be persisted. This is useful to quickly report on another value without changing the default configuration for future uses.

Users with the Owner or Editor role on a dashboard can click the Save button to persist the new value, which therefore becomes the default value (read here how to change other configurations).

Edit the association between a filter and insights

This section is addressed to users with the Owner or Editor role on a dashboard.

From the edit mode, you can click the filter name to select it (highlighted in purple). This allows you to quickly change how your filter will apply to each insight on your dashboard.

To do so, simply select the field that will be used for filtering on each insight card. Only fields matching your filter type will be available for selection.

In the GIF below, we can decide to apply the Reporting period filter on:

  • CLOSED AT for the Issue lead time for changes (on the left)

  • MERGED AT for the PR lead time for changes (in the middle)

  • PULL REQUEST > MERGED _AT for the Change Failure Rate (Commit-based) (on the right)

To help you select the most relevant filtering field, the dropdown will propose a set of suggested fields based on the filters and dimensions already used by each insight.

You can create as many filters as you need on your dashboard. Each filter will further refine the results on the associated insights.

Edit filters configurations

This section is addressed to users with the Owner or Editor role on a dashboard.

To fully edit your filters configurations so click on Edit dashboard on the top right of your screen then click the cogwheel icon on the right of your filter name to edit the configurations.

You can edit any of the configurations and save them to override the former configurations, by following the same process as creating a filter from scratch.

Filtering rules and precedence

Dashboard filters apply to insights and their drill down configuration.

Dashboard filters are added to pre-existing insight filters, using an AND combinator. Assuming a dashboard with three dashboarding filters, the resulting filtering query on each widget will be dashboard filter 1 AND dashboard filter 2 AND dashboard filter 3 AND insight filters.

Dashboard filters take precedence over insight filters. This means that if a dashboard filter is conflicting with an insight filter (i.e. the same field is used in both filters), the dashboard filter will override the insight filter.

E.g. 1

Configuration:

  • Insight filters: type = pull request

  • Dashboard filters: labels contain any of “bug” or “documentation”

Result: On the dashboard, the insight will have the resulting filters: type = pull request AND labels contain any of “bug” or “documentation”.

E.g. 2

Configuration:

  • Insight filters: none

  • Dashboard filters: project = “test/ux-ui” AND base_ref_branch =~ “hotfix/”.

Result: On the dashboard, the insight will have the resulting filters: project = “test/ux-ui” AND base_ref_branch =~ “hotfix/”

E.g. 3

Configuration:

  • Insight filters: merged_at > 6 months ago.

  • Dashboard filters: merged_at > 12 months ago.

Result: On the dashboard, the insight will have the resulting filters: merged_at > 12 month ago (dashboard filter takes precedence)

E.g. 4

Configuration:

  • Insight filters: type = issue and author = John Doe.

  • Dashboard filters: author = Bill Smith.

Result: On the dashboard, the insight will have the resulting filters: author = Bill Smith (dashboard filter takes precedence)

Dashboard filters examples & tips

E.g. 1: Report on the last quarter

Dashboard

Dashboard filter

  • Filter name: “Reporting period” will be the name under which the filter will be shown on the dashboard.

  • Type: “Date or time range” allows to target datetime fields.

  • Value: “Last 1 quarter” allows to filter datetime fields to the previous quarter.

Filter-to-insight association

  • On insight Pull request authors: select the CREATED AT field to retrieve pull requests created in the last quarter.

  • On insight Overdue items: select the DUE ON field to retrieve items whose due date is in the last quarter.

E.g. 2: Report on a specific user

Dashboard

The objective of this dashboard is to provide an overview of the engineering work that was done by a team, by looking at the pull requests or issues over a given time period.

Dashboard filter

  • Filter name: “Focus on user” will be the name under which the filter will be shown on the dashboard.

  • Type: “Text” allows to target single value text fields (e.g. author, merged_by).

  • Value: “jdoe” as default to show all PRs associated with “John Doe”. To show data associated with all users, you may change the operator to is not null instead.

Filter-to-insight association

For those insights, it is most logical to apply the dashboard filter to the AUTHOR field, since they describe personal work.

Insight & drilldown results

The results are now filtered on author = jdoe. Drilling down on an insight will also restrict results to items related to jdoe.

To see results across all users, you can simply change the dashboard filter to is not null. This is equivalent to asking “show me items for all users”.

E.g. 3: See the dashboard for specific projects, labels and types

Dashboard

The objective of this dashboard is to provide an overview of the spread of engineering force and labels over all imported projects.

Dashboard filter 1

  • Filter name: “Labels” will be the name under which the filter will be shown on the dashboard.

  • Type: “Text list” allows targeting fields that contain a list of text values (e.g. labels, assignees)

  • Value: “contains any of” is used to restrict the list of labels that contain at least one of the comma-separated values given in the input (bug, incident, documentation, feature, enhancement) in this case.

Dashboard filter 2

  • Filter name: “Project” will be the name under which the filter will be shown on the dashboard.

  • Type: “Text” allows to target fields that contain a single text value.

  • Value: In this case, we want to restrict the results to a single project : “Regular Space”. However, the Project field in the dataset only takes a simple text, not a list of text.

Filter-to-insight association

Both insights can be restricted to the chosen list of projects and labels, so both filters must be applied on the Label field and the Project field respectively.

Association for filter 1

Association for filter 2

Insight & drilldown results

Both insights and their drilldown reports restrict the results to the defined labels and project.

The filters can be widened by defining non-restrictive filters, such as:

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