Data Studio report templates (Google Analytics for Firebase)
Google Data Studio turns your raw Analytics data into informative reports that are easy to read, easy to share, and fully customizable. It does this by leveraging its BigQuery connector: after you link your Firebase app to BigQuery, your BigQuery dataset can be visualized beautifully in Data Studio.
To help get you started, we provide two sample reports that are based on a comprehensive set of metrics and dimensions available through your BigQuery schema. Use these samples as templates to quickly create your own reports and visualizations based on your own app’s raw data. Proceed by following the steps below.
Use a sample report template
- Start by choosing either the Events or the User Properties sample report.
- Click USE TEMPLATE in the upper right. The Create new report dialog appears.
- Map each Original Data Source to a corresponding New Data Source. If you’re just getting started with Data Studio, you should set up a new data source at this time by selecting from the corresponding New Data Source menu: BigQuery MY PROJECTS [Your Project] [Your Dataset] [Your Analytics table] and either Events or User Properties, depending on which sample report you started with.
- Once a valid source is selected, click CONNECT to create your new data source.
- Once your data source is created, click ADD TO REPORT to return back to the report template with your new datasource selected.
- Click CREATE REPORT.
You have now successfully created a copy of the sample report which uses your own Analytics BigQuery dataset! Follow the remaining steps to produce your reports.
Note the default date range
The sample report uses a default date range of Last 7 Days, and it compares metrics to the previous 7-day period.
Assuming your data source has the required data to support the selected date range, you will see the reports update automatically using your data. If you see “Configuration error” messages, this indicates that your data source does not have data to support the chosen date range and you should choose a different date or wait until your BigQuery dataset accumulates more daily tables.