How to connect Amazon QuickSight to Lakebase Data

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

CData Connect AI provides a pure cloud-to-cloud interface for Lakebase, allowing you to allowing build visualizations from Lakebase data in Amazon QuickSight. By importing your Lakebase 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.

Configure Lakebase Connectivity for Amazon QuickSight

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

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

2. Select "Lakebase" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Lakebase. To connect to Databricks Lakebase, start by setting the following properties:
   • DatabricksInstance: The Databricks instance or server hostname, provided in the format instance-abcdef12-3456-7890-abcd-abcdef123456.database.cloud.databricks.com.
   • Server: The host name or IP address of the server hosting the Lakebase database.
   • Port (optional): The port of the server hosting the Lakebase database, set to 5432 by default.
   • Database (optional): The database to connect to after authenticating to the Lakebase Server, set to the authenticating user's default database by default.

   OAuth Client Authentication

   To authenicate using OAuth client credentials, you need to configure an OAuth client in your service principal. In short, you need to do the following:

   1. Create and configure a new service principal
   2. Assign permissions to the service principal
   3. Create an OAuth secret for the service principal

   For more information, refer to the Setting Up OAuthClient Authentication section in the Help documentation.

   OAuth PKCE Authentication

   To authenticate using the OAuth code type with PKCE (Proof Key for Code Exchange), set the following properties:

   • AuthScheme: OAuthPKCE.
   • User: The authenticating user's user ID.

   For more information, refer to the Help documentation.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Lakebase 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 Lakebase data from Amazon QuickSight.

Import Lakebase Data into SPICE and Create Interactive Dashboards

The steps below outline creating a new data set based on the connection to Lakebase 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 Lakebase Data from Cloud Applications

At this point, you have a direct, cloud-to-cloud connection to Lakebase 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.