When you connect Panobi with your data in BigQuery, you’ll be able to see your team’s work side-by-side with the impact it’s making on your most important metrics.
Connecting BigQuery lets you...
see the effect of each release on your core business metrics like activation rate or DAU/MAU
contextualize metrics with concurrent real-world events like marketing campaigns and holidays
share consistent updates across your company
To complete the following steps, you’ll need permission to manage Identity and Access Management (IAM) in your Google Cloud Platform (GCP) project.
How to connect BigQuery with Panobi
These steps can also be found in your Panobi Integration Settings, if you have not yet configured this integration.
Create a service account
Log in to your account at https://console.cloud.google.com/iam-admin/serviceaccounts and select the correct project, if applicable, from the dropdown in the top left.
Click “+ Create Service Account” at the top.
Fill out the “Service account details”. Give it a name (we suggest “Panobi Integration”) and description, and click “Create and continue” (NOT “Done”).
Click in the Role dropdown, and start typing the words “BigQuery Job User” to filter and then select it.
Optional: Click “Continue” if you’d like to grant any teammates user or admin access to the service account.
Otherwise, click “Done”.
Generate a service account key
Back on the service account page, find the new service account you just created. Click the “Actions” menu for it, indicated by three dots on the right. Select “Manage keys” from the dropdown.
Click on the “Add Key” dropdown that appears. Select “Create new key” from the dropdown.
In the dialog that pops up, select “JSON” as the format of the key and click “Create”.
The key will then be saved as a file to your computer, named something like “name-of-project-######.json”.
Grant your service account access to datasets
In the main Google Cloud navigation menu in the top left, find the menu item “BigQuery” and open it in a new tab, leaving your “IAM & Admin” tab open.
Expand your project name in the “Explorer” section, and click on the dataset you’d like to permit Panobi to access.
When the dataset info has loaded on the right, click on the “Sharing” dropdown and select “Permissions”. A side panel will open from the right.
Before you proceed, switch back to your “IAM & Admin” tab. In the “Service accounts” list, hover over the email address given to your service account until you see an icon appear that allows you to copy the address to your clipboard.
Return to your “BigQuery” tab. In the open side panel, click the “+ Add principal” button.
In the “New principals” input field, paste the service account address copied to your clipboard.
In the “Role” dropdown, type “BigQuery Data Viewer” to filter and then select it.
Repeat the steps in this section for every dataset you’d like to make available to Panobi.
Upload your service account key to Panobi
In Panobi, navigate to your Settings, click on "Integrations", and choose BigQuery from the list of available integrations. Open the Configuration tab and find the input fields for the file name. Click on "Choose file" to browse your computer for the file containing your service account key, downloaded in Step 2 and named something like “name-of-project-######.json”.
After choosing the file, Panobi will show your Project ID. Click "Connect".
How to add a BigQuery metric
Click + Add metric on the Metrics page and select BigQuery from the data source dropdown. Then, paste the SQL query into the window, check that the correct columns of data have been returned, and choose the appropriate visualization.
Only metrics configured as a time series chart will be available on your timeline. This is how you should represent your KPI and OKR-level metrics such as “rate of activation” “new users” or “DAU”. You can also include other metrics you’re tracking, such as any baseline health indicators.
After creating your key metrics in Panobi, you can reference them quickly in any release or insight by typing # and typing to find the metric title. Remember to include information like which team or teams own the metric, the individual collaborators who contributed to the analysis, and any appropriate tags that will help someone find this metric in the future.
If you run into any issues with your BigQuery integration, check out our troubleshooting article for help diagnosing and fixing the problem.