How do you implement filters in your dashboard?

Dashboard Guide: Filters 

Filtering is an essential feature that allows users to interact with and explore data more efficiently by narrowing down the information displayed.  

Imagine you are a sales manager for a company with operations across multiple regions. You want to create a dashboard that allows you to analyze sales data by region, product category, and time period. 

Step 1: Identify the filtering criteria  

First, determine the criteria that users will need to filter the data. In our case, we want to filter by region, product category, and time period. List these criteria to guide your filter implementation. 

Step 2: Add filter widgets to the dashboard  

Most dashboarding tools provide a variety of filter widgets to enhance data exploration. Add the appropriate filter widgets to your dashboard based on your filtering criteria. Some common filter types include: 

  • Dropdown lists: Allow users to select a single option from a list. Ideal for our region and product category filters. 
  • Checkboxes: Enable users to select multiple options at once. Could be used for the product category filter if multiple categories need to be selected. 
  • Sliders: Allow users to choose a range of values by dragging a handle along a track. Useful for filtering continuous numeric data, like sales amounts or profit margins. 
  • Date range pickers: Let users select a specific date range. Perfect for our time period filter. 
  • Search boxes: Enable users to search for specific values or keywords within a dataset. Can be useful when filtering by customer names or other text-based data. 
  • Radio buttons: Allow users to select a single option among multiple choices. Similar to dropdown lists, but displays all options simultaneously. 
  • Multi-select lists: Similar to checkboxes, but presented in a list format. Users can select multiple options by holding down the Ctrl (or Cmd) key while clicking. 
  • Toggle switches: Enable users to turn a filter on or off. Can be used for binary filterings, such as showing only items that meet a specific condition (e.g., products with discounts).

For our example, you may use: 

  • Dropdown list for regions 
  • Dropdown list or checkboxes for product categories 
  • Date range picker for the time period 

Step 3: Connect the filter widgets to the data source  

Link the filter widgets to your dashboard’s data source or specific visualizations. Configure the widgets to filter the data based on the user’s selection. For instance, when users select a region from the dropdown list, the dashboard should display data only for that region. 

Step 4: Configure filter interactions  

Set up the interactions between multiple filters, if necessary. In our example, if a user filters by region and product category simultaneously, the dashboard should display data that meets both criteria. 

Step 5: Test the filters  

Ensure the filters are working as expected by testing different combinations of filter selections. Verify that the data displayed in the dashboard updates accordingly and that the visualizations maintain their integrity. 

Step 6: Optimize filter performance  

Depending on the size of your dataset, filters can impact dashboard performance. Optimize the performance by: 

  • Limiting the number of available filter options 
  • Implementing server-side filtering, if possible 
  • Pre-aggregating or summarizing the data before applying filters 

Helpful tips and tricks: 

  1. Use clear labels for filter widgets to help users understand what each filter does. 
  2. If your dashboard includes multiple visualizations, consider using global filters that affect all visualizations or local filters that only apply to specific visualizations. 
  3. To enhance user experience, consider using dynamic filters that update based on the user’s previous filter selections. 

Related Tags: