When it comes to building dashboards, a common request from our clients is to have different date filters affect different sections of the dashboard. While this might help meet some departmental data visualization requirements, this practice can be confusing from a usability standpoint. Static text boxes could be added to divide the dashboard into sections providing better context on which filter is used to control which section. However, a better approach would be to add a Dynamic Date Tile to your dashboard that can provide clarity by highlighting the date range currently being used as a filter for the defined section. In this post, we will explore how to successfully do this within Looker.

Start with LookML Adjustments

Begin by adjusting the base lookml to display a range of values when the date filter is not set (date_range is null). In the example case shown below, we have adjusted the case statement to use the start and end dates of the current year.

Note: Using Google BigQuery Standard SQL

Dashboard Filter Set-up

The next thing you need to do is set up your dashboard filter. Create a single value tile based on the display_date_range dimension which will display the value the user selects in the next step.  

Once you have added the Dynamic Date Tile, add a new date filter to the dashboard. Then, edit the filter to apply to the specified tiles on the dashboard including the previously added single value tile. See screenshot below for an example of how to configure within Looker.

Why Dynamic Date Tiles?

Dynamic Date Tiles make it easier to understand the current date range applied to that section of the dashboard reducing overall confusion for users. This complexity can be compounded if there is more than one date range filter applied to a dashboard creating the need for something like a Dynamic Date Tile.

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Naveed

 

Naveed is data engineer and analyst with a sharp eye on business outcomes. Combined with excellent communication, he will drive any organization to become more data driven.


Data Clymer is a premier consulting firm specializing in full-stack analytics and data culture transformation. Our proven methodology includes full data stack implementation, data democratization, custom training, and analytics to enable data-driven decisions across the organization. We have curated a set of best practices from our deep expertise in Snowflake, Sigma, Looker, Matillon, DBT, Fivetran, Tableau, BigQuery, and more. 

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