How to connect Amazon QuickSight to MySQL 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 MySQL data for visualizations, dashboards, and more. This article shows how to connect to MySQL in Connect AI and build dashboards in Amazon QuickSight with access to MySQL data.

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

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

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

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

3. Enter the necessary authentication properties to connect to MySQL.

   The CData Provider supports connecting to on-premises and cloud-hosted versions of MySQL such as Amazon RDS for MySQL, Google Cloud SQL for MySQL, Azure Database for MySQL, or Oracle MySQL HeatWave. The Server and Port properties must be set to a MySQL server. If IntegratedSecurity is set to false, then User and Password must be set to valid user credentials. Optionally, Database can be set to connect to a specific database. If not set, tables from all databases will be returned.

   SSH Connectivity for MySQL

   You can use SSH (Secure Shell) to authenticate with MySQL, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).

   SSH Connections to MySQL in Password Auth Mode

   To connect to MySQL via SSH in Password Auth mode, set the following connection properties:

   • User: MySQL User name
   • Password: MySQL Password
   • Database: MySQL database name
   • Server: MySQL Server name
   • Port: MySQL port number like 3306
   • UserSSH: "true"
   • SSHAuthMode: "Password"
   • SSHPort: SSH Port number
   • SSHServer: SSH Server name
   • SSHUser: SSH User name
   • SSHPassword: SSH Password

   SSH Connections to MySQL in Public Key Auth Mode

   To connect to MySQL via SSH in Password Auth mode, set the following connection properties:

   • User: MySQL User name
   • Password: MySQL Password
   • Database: MySQL database name
   • Server: MySQL Server name
   • Port: MySQL port number like 3306
   • UserSSH: "true"
   • SSHAuthMode: "Public_Key"
   • SSHPort: SSH Port number
   • SSHServer: SSH Server name
   • SSHUser: SSH User name
   • SSHClientCret: the path for the public key certificate file
   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add MySQL 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 MySQL data from Amazon QuickSight.

Import MySQL Data into SPICE and Create Interactive Dashboards

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

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