Analyze Google Cloud Storage Data in Looker

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use CData Connect AI to connect to Google Cloud Storage Data from Looker and build custom apps using live Google Cloud Storage data.

Looker is a business intelligence and big data analytics platform that helps you explore, analyze and share real-time business analytics. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Google Cloud Storage data for business applications. This article shows how to connect to Google Cloud Storage in Connect AI and then connect to Google Cloud Storage data in Looker.

CData Connect AI provides a pure cloud-to-cloud interface for Google Cloud Storage, allowing you to build reports from live Google Cloud Storage data in Looker — without replicating the data to a natively supported database. As you create applications to work with data, Looker generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc.) directly to Google Cloud Storage, leveraging server-side processing to quickly return the requested Google Cloud Storage data.

Configure Google Cloud Storage Connectivity for Looker

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "Google Cloud Storage" from the Add Connection panel
  4. Selecting a data source
  5. 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.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add Google Cloud Storage Connection page and update the User-based permissions. Updating 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. Creating a new PAT
  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 Looker.

Connect to Google Cloud Storage in Looker

The steps below outline connecting to CData Connect AI from Looker to create a new Google Cloud Storage data source.

  1. Log-in to Looker
  2. In the navigation pane, select Admin. Selecting Admin
  3. Under the Database category, select Connections. Selecting connections
  4. On the Connections page, click Add Connection. Adding a new connection
  5. Enter the connection settings:
    • Name: the name for the connection in models.
    • Dialect: select Microsoft SQL Server 2017+.
    • SSH Server: leave this disabled.
    • Remote Host:Port: enter tds.cdata.com in the first field and 14333 in the second field.
    • Database: enter the Connection Name of the CData Connect AI data source you want to connect to (for example, QuickBooksOnline1).
    • Username: enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected]
    • Password: enter the PAT you generated on the Settings page
    Leave the rest of the connection settings at their default values unless you need to modify them. Configuring connection settings
  6. At the bottom of the page, click Test These Settings to ensure that you can connect to CData Connect AI.
  7. Click Add Connection to create the connection and return to the Connections page. New connection added.

Your connection is now available for use in Looker. To connect to additional data sources from your CData Connect AI account, repeat the setup steps above, changing the value for Database for each data source.

Creating A Looker Visualization From The SQL Runner and Explore Features

To create a visualization in Looker using the SQL Runner, follow these steps:

  1. In the Looker interface, select Develop -> SQL Runner from the left navigation pane. Select SQL Runner.
  2. On the SQL Runner interface, select the connection you made in the previous steps. Entering name for new dashboard.
  3. Now, click the gear symbol next to a table and then select Explore Table. Entering name for new dashboard.
  4. Next, on the left menu, select fields from the table and click Run. You can now expand the Visualization accordion, and see a bar chart, by default. Entering name for new dashboard.

    We have now created a visualization of Google Cloud Storage data in Looker using CData Connect AI!

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