Control Your Data View with Dashboard Filters
Dashboard filters let you dynamically control what data appears in your visualizations. Add time-based or dimension-based filters to transform static dashboards into flexible analytics tools that answer different questions.
What You'll Learn
Add time period and time frame filters
Create global filters based on data columns
Apply filters to specific tiles only
Allow runtime filter overrides
Resolve filter conflicts
Two Types of Dashboard Filters
1. Time-Based Filters
Time filters control the date range and grouping of your data.
Time Period Filter:
Controls the date range (last 90 days, this quarter, etc.)
Applied globally across the dashboard
Can be customized per tile
Time Frame Filter:
Controls data grouping (daily, weekly, monthly)
Changes how data is aggregated
Affects trend visualizations
To Add a Time Filter:
Enter dashboard edit mode
Select your time period (e.g., "Last 90 days")
Choose which tiles should receive the filter
Select time frame grouping if needed
Save your changes
2. Data Column Filters
Filter your dashboard based on any dimension in your data model.
Adding a Column Filter:
Enter edit mode
Click the plus (+) button to add a filter
Choose the appropriate column (e.g., "Product Type")
Select your filter logic based on data type
Filter Options by Data Type:
Text/String Fields:
Equal to
Not equal to
Contains
Does not contain
In list
Not in list
Numeric Fields:
Equal to
Greater than
Less than
Between
Not equal to
Date Fields:
Before
After
Between
Last X days/months
This period
Applying Filters to Specific Tiles
By default, filters apply to all dashboard tiles. You can customize this for more control.
To Customize Filter Application:
Click on the filter in edit mode
Select "Choose specific tiles"
Check only the tiles that should receive this filter
Ensure the column exists in those tiles' data
Save your edits
Example Scenario: You have a dashboard with sales and inventory tiles. Apply a "Region = West" filter only to sales tiles while showing all regions for inventory.
Filter Behavior and Overrides
Saved Filter Values
Filters saved with the dashboard load automatically
Provide consistent default views for all users
Ensure everyone starts with the same data perspective
Runtime Overrides
Users can change filter values without editing the dashboard
Changes are temporary and don't affect saved settings
Reset to defaults by refreshing the dashboard
User Workflow
Dashboard loads with saved filter values
User adjusts filters for their current needs
Analysis happens with customized view
Next load returns to saved defaults
Best Practices
Filter Strategy
Start Broad, Then Narrow:
Begin with longer time periods
Add specific filters as needed
Keep commonly used filters saved
Consider Your Audience:
Sales teams might need region filters
Product teams might need category filters
Executives might need time comparisons
Performance Tips
Fewer filters = faster dashboard loads
Use tile-specific filters when possible
Avoid redundant filtering at tile and dashboard levels
Avoiding Filter Conflicts
Filters can exist at both dashboard and individual tile levels, which may cause conflicts.
Common Conflict Scenarios
Scenario 1: Overlapping Date Ranges
Dashboard filter: Last 30 days
Tile filter: Last 90 days
Result: More restrictive filter wins (30 days)
Scenario 2: Contradicting Dimensions
Dashboard filter: Region = "West"
Tile filter: Region = "East"
Result: No data shown (impossible condition)
Resolving Conflicts
Review Tile Filters:
Edit individual tiles
Remove conflicting tile-level filters
Let dashboard filters control the view
Use Tile Exclusions:
Exempt specific tiles from dashboard filters
Maintain tile independence when needed
Document Filter Logic:
Note which tiles have special filtering
Communicate logic to dashboard users
Practical Examples
Sales Dashboard
Time Filter: Last Quarter
Column Filter: Product Type = "Electronics"
Applied to: All tiles except YoY comparison
Regional Performance
Time Filter: This Month, grouped Weekly
Column Filter: Region (user selectable)
Applied to: Sales and customer tiles only
Executive Summary
Time Filter: YTD vs Prior YTD
Column Filter: None (showing all data)
Applied to: All tiles
Troubleshooting
Filters not working?
Verify the column exists in the tile's data
Check for conflicting tile-level filters
Ensure proper filter syntax
Dashboard loading slowly?
Reduce the number of global filters
Use more specific time ranges
Consider tile-specific filters instead
Data not showing?
Check if filter combination is too restrictive
Verify filter values exist in your data
Review both dashboard and tile filters
You're Ready!
Start by adding a simple time filter to one of your dashboards. Set it to "Last 30 days" and see how it changes your visualizations. Then try adding a column filter for a dimension you frequently analyze.
Your first challenge:
Open a dashboard you use regularly
Add a time filter for the last 90 days
Add one column filter for a key dimension
Apply the column filter to only half the tiles
Save and test the interactive filtering