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URL: https://www.cdata.com/kb/tech/bigquery-cloud-quicksight.rst

⇱ How to connect Amazon QuickSight to BigQuery Data

How to connect Amazon QuickSight to BigQuery Data

👁 Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Create a connection to BigQuery data in CData Connect AI and insert BigQuery data into Amazon QuickSight SPICE to build interactive dashboards.

Amazon QuickSight allows users to build interactive dashboards in the cloud. When paired with CData Connect AI, you get cloud-to-cloud access to BigQuery data for visualizations, dashboards, and more. This article shows how to connect to BigQuery in Connect AI and build dashboards in Amazon QuickSight with access to BigQuery data.

CData Connect AI provides a pure cloud-to-cloud interface for BigQuery, allowing you to allowing build visualizations from BigQuery data in Amazon QuickSight. By importing your BigQuery data into the Amazon QuickSight "Super-fast, Parallel, In-memory Calculation Engine" (SPICE), you can leverage the powerful data processing features of the Amazon ecosystem to build responsive dashboards. And with the ability to schedule refreshes of the data stored in SPICE, you control how up-to-date your dashboards are.

About BigQuery Data Integration

CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:

  • Simplify access to BigQuery with broad out-of-the-box support for authentication schemes, including OAuth, OAuth JWT, and GCP Instance.
  • Enhance data workflows with Bi-directional data access between BigQuery and other applications.
  • Perform key BigQuery actions like starting, retrieving, and canceling jobs; deleting tables; or insert job loads through SQL stored procedures.

Most CData customers are using Google BigQuery as their data warehouse and so use CData solutions to migrate business data from separate sources into BigQuery for comprehensive analytics. Other customers use our connectivity to analyze and report on their Google BigQuery data, with many customers using both solutions.

For more details on how CData enhances your Google BigQuery experience, check out our blog post: https://www.cdata.com/blog/what-is-bigquery


Getting Started


Configure BigQuery Connectivity for Amazon QuickSight

Connectivity to BigQuery from Amazon QuickSight is made possible through CData Connect AI. To work with BigQuery data from Amazon QuickSight, we start by creating and configuring a BigQuery connection.

  1. Log into Connect AI, click Sources, and then click Add Connection
    2. 👁 Adding a Connection
  2. Select "BigQuery" from the Add Connection panel
    3. 👁 Selecting a data source
  3. BigQuery uses OAuth to authenticate. Click "Sign in" to authenticate with BigQuery. 👁 Authenticating with OAuth (Salesforce is shown).
  4. Navigate to the Permissions tab in the Add BigQuery 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 BigQuery data from Amazon QuickSight.

Import BigQuery Data into SPICE and Create Interactive Dashboards

The steps below outline creating a new data set based on the connection to BigQuery in Connect AI, importing the dataset into SPICE, and building a simple visualization from the data.

  1. Log into Amazon QuickSight and click "Manage data."
  2. Click "Now data set," select SQL Server as the data source, configure the connection to your Connect AI instance, and click "Create data source." 👁 Connecting to Connect AI as a QuickSight data set.
  3. Select a table to visualize (or subait a custom SQL query for your data). 👁 Selecting a Table to visualize.
  4. Click "Edit/Preview data" to customize the data set.
  5. Select "Import to SPICE for quicker analytics" and click "Visualize." 👁 Importing data to SPICE for quicker analytics.
  6. Select fields to visualize and a visual type. 👁 Visualizing data in QuickSight via Connect AI (Salesforce is shown).

Schedule Refreshes for SPICE Data Sets

QuickSight users can schedule refreshes for data sets that are imported into SPICE, ensuring that data being analyzed is only as old as the most recent refresh.

  1. Navigate to the QuickSight home page.
  2. Click "Manage data."
  3. Select the data set you wish to refresh.
  4. Click "Schedule refresh."
  5. Click Create, configure the refresh settings (time zone, repeat frequency, and starting datetime), and click Create. 👁 Scheduling a refreshing of the data imported into SPICE.

Live Access to BigQuery Data from Cloud Applications

At this point, you have a direct, cloud-to-cloud connection to BigQuery data from your Amazon QuickSight dashboard. You can create new visualizations, build interactive dashboards, and more. For more information on gaining live access to data from more than 100 SaaS, Big Data, and NoSQL sources from cloud applications like Amazon QuickSight, refer to our Connect AI page.