How to integrate Metabase with Google Cloud Storage Data

Metabase is an open source data visualization tool that allows users to create interactive dashboards. When paired with CData Connect AI, users can easily create visualizations and dashboards linked to live Google Cloud Storage data. This article describes how to connect to Google Cloud Storage and build a simple visualization using Google Cloud Storage data.

CData Connect provides a pure cloud-to-cloud interface for Google Cloud Storage, allowing you to easily integrate with live Google Cloud Storage data in Metabase — without replicating the data. Connect looks exactly like a SQL Server database to Metabase and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to Google Cloud Storage, leveraging server-side processing to quickly return Google Cloud Storage data.

Configure Google Cloud Storage Connectivity for Metabase

Connectivity to Google Cloud Storage from Metabase is made possible through CData Connect AI. To work with Google Cloud Storage data from Metabase, we start by creating and configuring a Google Cloud Storage connection.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Google Cloud Storage" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Google Cloud Storage.

   Authenticate with a User Account

   You can connect without setting any connection properties for your user credentials. After setting InitiateOAuth to GETANDREFRESH, you are ready to connect.

   When you connect, the Google Cloud Storage OAuth endpoint opens in your default browser. Log in and grant permissions, then the OAuth process completes

   Authenticate with a Service Account

   Service accounts have silent authentication, without user authentication in the browser. You can also use a service account to delegate enterprise-wide access scopes.

   You need to create an OAuth application in this flow. See the Help documentation for more information. After setting the following connection properties, you are ready to connect:

   • InitiateOAuth: Set this to GETANDREFRESH.
   • OAuthJWTCertType: Set this to "PFXFILE".
   • OAuthJWTCert: Set this to the path to the .p12 file you generated.
   • OAuthJWTCertPassword: Set this to the password of the .p12 file.
   • OAuthJWTCertSubject: Set this to "*" to pick the first certificate in the certificate store.
   • OAuthJWTIssuer: In the service accounts section, click Manage Service Accounts and set this field to the email address displayed in the service account Id field.
   • OAuthJWTSubject: Set this to your enterprise Id if your subject type is set to "enterprise" or your app user Id if your subject type is set to "user".
   • ProjectId: Set this to the Id of the project you want to connect to.

   The OAuth flow for a service account then completes.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Google Cloud Storage Connection page and update the User-based permissions.

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Google Cloud Storage data from Metabase.

Connect to CData Connect AI from Metabase

After creating the connection in Connect AI, navigate to your Metabase instance. Use the SQL Server interface to connect to Connect AI.

1. Navigate to the administration screen (Settings -> Admin) and click "Add Database" from the "Databases" tab
2. Configure the connection to Connect AI and click "Save"
   • Database type: Select "SQL Server"
   • Name: Name the connection (e.g. "Google Cloud Storage (Connect AI)")
   • Host: tds.cdata.com
   • Port: 14333
   • Database name: The name of the connection you just created (e.g. GoogleCloudStorage1)
   • Username: A Connect AI username (e.g. [email protected])
   • Password: The PAT previously created
   • Click to Use a secure connection (SSL)
   

Execute Google Cloud Storage Data with Metabase

Once you configure the connection to Connect AI, you can query Google Cloud Storage and build visualizations.

1. Use the "Write SQL" tool to retrieve the Google Cloud Storage data
2. Write a SQL query based on the Google Cloud Storage connection in CData Connect AI, e.g.
   
   

   SELECT Name, OwnerId FROM Buckets WHERE Name = 'TestBucket'

   
3. Navigate to the "Visualization" screen, choose a visualization, and configure the visualization

More Information & Free Trial

At this point, you have built a simple visualization from Google Cloud Storage data in Metabase. You can continue to work with live Google Cloud Storage data in Metabase just like you would any SQL Server database. For more information on creating a live connection to Google Cloud Storage (and more than 100 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Google Cloud Storage data in Metabase today.