Using drilldown
Tom Azernour avatar
Written by Tom Azernour
Updated over a week ago

How to view the drilldown?

The Drilldown feature allows you to explore and analyze data from a particular insight in detail. It is accessed by clicking on specific data points in your insights.

The drilldown option can be activated for most types of insights, such as Charts, KPIs, and Reports, as long as they include an aggregation metric (COUNT, AVG, SUM, etc.)

To access the drilldown feature, click on a data point on an insight from a dashboard. The drilldown table opens revealing the data, according to the configuration defined.

By default, the feature is activated and configured for most insights templates. That means the option is ready to use when creating a dashboard or an insight from a template.

However, the option must be activated and configured for insights created from scratch (see How to enable & configure the drilldown 👇).

How to enable & configure the drilldown?

Drilldown is optional and can be enabled and configured for individual insights.

Configure it from the Configure drilldown tab on the left panel, while configuring a chart, a report, or a KPI insight.

This interface is dedicated to the drilldown table configuration. The drilldown can be enabled by clicking the toggle button.

The preview on the top part of the screen shows the actual results of clicking a data point on your insight.

When enabled the first time, a default configuration is applied with:

  • A set of recommended columns

  • Pre-configured filters matching the clicked data point.

To get you started, the first data point of your insight will be selected to populate the preview of the drilldown table. You can click another point from the insight configuration tab to preview the drilldown table with another data point.

Apply recommended configuration

You can revert all changes made to your drilldown table and get back to the suggested configuration by clicking Apply recommended config. This is useful to apply changes you made to the actual insight (e.g. changes in columns and filters).

Clicking Apply recommended config will overwrite both columns and filter configurations.

In the situation where you need to revert only the suggested columns or filters, use the dropdown on the right of the button and click Apply for columns only or Apply for filters only to keep other configurations unchanged.

Change the filters: target your clicked datapoint

The central point in the drilldown configuration is the dynamic filtering value. It allows you to filter a set of records based on the attributes of the data point that was clicked on in an insight (e.g. a point on a chart, a cell in a heatmap, a bar in a column chart).

This dynamic filtering system allows you to “zoom” on a group of records using a clicked data point.

While dynamic filtering is at the center of configuring the drilldown behavior (it is the actual drill “down” part), conventional (“static”) filtering can also be performed to further refine the drilled-down records (e.g. I only want to see pull requests labeled as “bug” when I drilldown on this specific date). You can read more about the filtering system here.

Change the columns: choose your drilldown information

Configuring columns on a drilldown report is done the same way as configuring a regular report insight.

You can add multiple dimensions and metrics. To add them, simply click on the (+) sign button on the right side of the column and select “dimension” or “metric”. To delete dimensions and/or metrics columns, click on the expand (...) button and select the Delete option.

You can perform basic or advanced queries. Select the fields you want to query from the drop-down menu at the top of the Dimension column or choose Custom formula. From the drop-down menu at the top of the Metric column, choose operator, aggregator, or Custom formula.

Example: how the “Apply recommended config” works

The recommended configuration works by applying “standard rules” that one would expect to use when drilling down on a specific range of data. It is therefore a good example by itself, which you can use as a basis to further refine the drilldown behavior of your insight.

Let’s consider an insight that counts the number of pull requests merged per month.

This insight is configured with the following filters:

Now when I click on a specific value (December 2022 in the screenshot above), I would expect to see all the merged pull requests for that specific month. Luckily, this is exactly what the recommended configuration will do.

The recommended configuration applies the following rules to filter drilled-down records:

  • All dimensions in your insight are used as dynamic filters (in green below) based on the selected data point. In this example, we have one dimension merged_at with a granularity set to Year > Month - this is what is used as a dynamic filter. When you click December 2022, the dynamic filter will match all records where the merged_at value matches “December 2022”

  • All filters in your insight get applied as static filters (in orange below) on your drilled-down records. In this example, the conditions on type = pull request and merged_at in last 6 months will therefore be applied to your drilled-down records as is.

This recommended logic results in the following filters for the drilled-down records:

The recommended configuration also selects all dimensions that were originally in your insight and uses these dimensions as display columns for the drilled-down records. Using the example above, the recommended configuration will only select the “merged at” field as a column.

This minimal display configuration can then be enhanced with other content fields, such as:

  • The title of the pull request

  • The URL of the pull request

The final drilldown configuration will look like this:

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