Create Google Cloud Storage-Connected Visualizations in Klipfolio

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

Klipfolio is an online dashboard platform designed to create real-time business dashboards, whether for your team or clients. When combined with CData Connect AI, you gain immediate cloud-to-cloud access to Google Cloud Storage data to create visualizations, reports, and more. This article provides step-by-step instructions on connecting to Google Cloud Storage within Connect AI and creating visualizations using Google Cloud Storage data in Klipfolio.

CData Connect AI offers a direct cloud-to-cloud interface for Google Cloud Storage, enabling you to construct reports from real-time Google Cloud Storage data data within Klipfolio—without the need for data replication to a database natively supported by Klipfolio. While building visualizations, Klipfolio generates SQL queries to fetch data. With optimized data processing capabilities out of the box, CData Connect AI efficiently directs all supported SQL operations (such as filters, JOINs, etc.) directly to Google Cloud Storage, harnessing server-side processing to swiftly retrieve the requested Google Cloud Storage data data.

Configure Google Cloud Storage Connectivity for Klipfolio

Connectivity to Google Cloud Storage from Klipfolio is made possible through CData Connect AI. To work with Google Cloud Storage data from Klipfolio, 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 Klipfolio.

Connect to Google Cloud Storage from Klipfolio

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

  1. Open Klipfolio
  2. Click in Data Sources to add a new data source
  3. Search for and select MSSQL as the Service Adding a new datasource.
  4. Click "Create a custom MSSQL data source"
  5. Configure the data source by setting the MSSQL connection properties:
    • Host: tds.cdata.com
    • Port: 14333
    • Database: your database (e.g., GoogleCloudStorage1)
    • Driver: MS SQL
    • Username: a Connect AI user (e.g. [email protected])
    • Password: the above user's PAT
    • SQL Query: any query to retrieve data (e.g. SELECT * FROM Buckets )
    • Select the checkbox to "Include column headers"
    • Select the checkbox to "Use SSL/TLS"
    Configuring the connection to Connect AI.
  6. Click "Get data" to preview the Google Cloud Storage data before building a data model.

Build a Data Model

After retrieving the data, click the checkbox to "Model your data" and click "Continue." In the new window, configure your data model.

  1. Confirm that the model includes all columns you wish to work with
  2. Name your model
  3. (optional) Set the Description
  4. Set "Header in row" to 1
  5. Click the toggle to "Exclude data before row" and set the value to 2
  6. Click "Save and Exit" Configuring the data model.

Create a Metric

With the data modeled, we are ready to create a Metric (or visualization) of the data to be used in the Klipfolio platform for dashboards, reporting, and more.

  1. Click "Create metrics"
  2. Select a Data source
  3. Select a Metric value and default aggregation
  4. Select Segmentation(s)
  5. Select a Date & time
  6. Select a Data shape
  7. Configure the Display settings
  8. Click Save Configuring a Metric
  9. Navigate to your Metric and further configure the visualization A configured Metric

SQL Access to Google Cloud Storage Data from Cloud Applications

Now you have a Metric built from live Google Cloud Storage data. You can add it to a new dashboard, share, and more. Easily create more data sources and new visualizations, produce reports, and more — all without replicating Google Cloud Storage data.

To get SQL data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI.

Ready to get started?

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