App filter
A metric level filter designed specifically for controlling access to individual metrics. Unlike general RLS settings. It restricts access without requiring end user input or control.
Last updated
A metric level filter designed specifically for controlling access to individual metrics. Unlike general RLS settings. It restricts access without requiring end user input or control.
Last updated
Question: What is the purpose of implementing an app filter?
Answer: The purpose of implementing an app filter is to ensure that specific data access is controlled based on client requirements, while preventing end users from modifying the filter settings. For instance, in a retail analytics application, an app filter could be used to restrict access to sales data by region, allowing regional managers to view only the data relevant to their territories without the ability for individual store managers to alter the filter criteria.
Question: How can we create an app filter? Answer: Please follow the steps outlined below.
Step 1: Let's begin by creating a metric.
Step 2: Next, let's create a metric-level filter of the type Guest Token.
Step 3: Choose the appropriate filter variant based on your requirements, then add options to test them on the DataBrain app.
Step 4: Click "Next" to proceed to the application section. Select the dataset and column to which you want to apply the filter.
Step 5: Click "Save." To test the filter, you'll notice a filter popup on the right side. Please note that these filter controls are visible on the metric page of the DataBrain app but won't be visible on metric cards or embedded metrics to end users.
