Build AI/ML Models with Live PingOne Data using Dataiku

Dataiku is a data science and machine learning platform used for data preparation, analysis, visualization, and AI/ML model deployment, enabling collaborative and efficient data-driven decision-making. When paired with the CData JDBC Driver for PingOne, Dataiku enhances data integration, preparation, real-time analysis, and reliable model deployment for PingOne data.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live PingOne data. When you issue complex SQL queries to PingOne, the driver pushes supported SQL operations, like filters and aggregations, directly to PingOne and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze PingOne data using native data types.

This article shows how you can easily integrate to PingOne using CData JDBC Driver for PingOne in Dataiku DSS (Data Science Studio) platform, allowing you to prepare the data and build custom AI/ML models.

Preparing the Dataiku DSS environment

In this section, we will explore how to set up Dataiku, as previously introduced, with PingOne data. Be sure to install Dataiku DSS (On-Prem version) for your preferred operating system, beforehand.

Install the CData JDBC Driver for PingOne

First, install the CData JDBC Driver for PingOne on the same machine as Dataiku. The JDBC Driver will be installed in the following path:

C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.pingone.jar

Connecting the JDBC Driver in Dataiku DSS

To use the CData JDBC driver in Dataiku, you must create a new SQL database connection and add the JDBC Driver JAR file in the DSS connection settings.

1. Log into Dataiku DSS platform. It should open locally in your browser (e.g. localhost:11200) 👁 Log into Dataiku DSS platform.
   👁 Dataiku DSS platform dashboard.
   
2. Click on Navigate to other sections of Dataiku menu on the top right section of the platform and select Administration. 👁 Select Administration.
   
3. Select the Connections tab. 👁 Select Connections.
   
4. In Connections, click on New Connections button. 👁 Click New Connections.
   
5. Now, scroll down and select Other SQL databases. 👁 Select Other SQL databases.
   

6. Generate a JDBC URL for connecting to PingOne, beginning with jdbc:pingone: followed by a series of semicolon-separated connection string properties.

   To connect to PingOne, configure these properties:

   • : The region where the data for your PingOne organization is being hosted.
   • : The type of authentication to use when connecting to PingOne.
   • Either (required when using the default PingOne domain) or , configured as described below.

   Configuring WorkerAppEnvironmentId

   is the ID of the PingOne environment in which your Worker application resides. This parameter is used only when the environment is using the default PingOne domain (auth.pingone). It is configured after you have created the custom OAuth application you will use to authenticate to PingOne, as described in Creating a Custom OAuth Application in the Help documentation.

   First, find the value for this property:

   1. From the home page of your PingOne organization, move to the navigation sidebar and click Environments.
   2. Find the environment in which you have created your custom OAuth/Worker application (usually Administrators), and click Manage Environment. The environment's home page displays.
   3. In the environment's home page navigation sidebar, click Applications.
   4. Find your OAuth or Worker application details in the list.
   5. Copy the value in the Environment ID field. It should look similar to:
      

      WorkerAppEnvironmentId='11e96fc7-aa4d-4a60-8196-9acf91424eca'

   Now set to the value of the Environment ID field.

   Configuring AuthorizationServerURL

   is the base URL of the PingOne authorization server for the environment where your application is located. This property is only used when you have set up a custom domain for the environment, as described in the PingOne platform API documentation. See Custom Domains.

   Authenticating to PingOne with OAuth

   PingOne supports both OAuth and OAuthClient authentication. In addition to performing the configuration steps described above, there are two more steps to complete to support OAuth or OAuthCliet authentication:

   • Create and configure a custom OAuth application, as described in Creating a Custom OAuth Application in the Help documentation.
   • To ensure that the driver can access the entities in Data Model, confirm that you have configured the correct roles for the admin user/worker application you will be using, as described in Administrator Roles in the Help documentation.
   • Set the appropriate properties for the authscheme and authflow of your choice, as described in the following subsections.

   OAuth (Authorization Code grant)

   Set to OAuth.

   Desktop Applications

   Get and Refresh the OAuth Access Token

   After setting the following, you are ready to connect:

   • : GETANDREFRESH. To avoid the need to repeat the OAuth exchange and manually setting the each time you connect, use .
   • : The Client ID you obtained when you created your custom OAuth application.
   • : The Client Secret you obtained when you created your custom OAuth application.
   • : The redirect URI you defined when you registered your custom OAuth application. For example: https://localhost:3333

   When you connect, the driver opens PingOne's OAuth endpoint in your default browser. Log in and grant permissions to the application. The driver then completes the OAuth process:

   1. The driver obtains an access token from PingOne and uses it to request data.
   2. The OAuth values are saved in the location specified in , to be persisted across connections.

   The driver refreshes the access token automatically when it expires.

   For other OAuth methods, including Web Applications, Headless Machines, or Client Credentials Grant, refer to the Help documentation.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the PingOne JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.pingone.jar
   

   Fill in the connection properties and copy the connection string to the clipboard.

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

   A typical JDBC URL is given below:

   jdbc:pingone:AuthScheme=OAuth;WorkerAppEnvironmentId=eebc33a8-xxxx-4f3a-yyyy-d3e5262fd49e;Region=NA;OAuthClientId=client_id;OAuthClientSecret=client_secret;InitiateOAuth=GETANDREFRESH;
   

7. On the New SQL database (JDBC) connection screen, enter a name in the New connection name field and specify the basic parameters:
   • JDBC Driver Class: cdata.jdbc.pingone.PingOneDriver
   • JDBC URL: JDBC connection URL obtained in the previous step
   • Driver jars directory: the folder path where the JAR file is installed on your system
   👁 Enter a connection name and specify the basic connection parameters.
   

   Next, select the SQL dialect of your choice. Here, we have selected 'SQL Server' as the preferred dialect. Click on Create. If the connection is successful, a prompt will display, saying 'Connection OK'.

8. The Data Catalog window will appear. Select the desired connection, catalog, and schema from the Connection to browse, Restrict to catalog, and Restrict to schema dropdowns, then click on List Tables. The Dataiku platform will list all the required tables. 👁 Select the connection, catalog and schema to filter the list of tables.
   👁 Data Catalog lists all the available tables in the datasource.
   
9. Select any table from the list and click Preview to view the table data. Click Close to exit the window. 👁 Preview any specific table data.
   

Creating a new project

To prepare data flows, create dashboards, analyze the PingOne data, and build AI and ML models in the Dataiku DSS platform, you need to first create a new project.

1. Select Projects from the Navigate to other sections of Dataiku menu. 👁 Select Project.
   
2. In the Projects screen, click New Project and select + Blank Project. 👁 Select a Blank Project.
   
3. In the New Project window, assign a Name and Project Key. Click Create. The new project dashboard opens up. 👁 Enter a Name and Project Key.
   👁 Project dashboard is displayed.
   
4. Select Notebooks from the menu at the top of the project screen. 👁 Select Notebooks.
   
5. Click on + Create Your First Notebook dropdown menu and select Write your own option. 👁 Create the notebook.
   
6. In the New Notebook window, select SQL. 👁 Select SQL.
   
7. Now, select the required connection from the Connection dropdown and enter a name in the Notebook Name field. 👁 Select a connection and add a notebook name.
   

Testing the connection

To test the PingOne connection and analyze the PingOne data, write a query in the query compiler and click Run. The queried/filtered PingOne data results will then appear on the screen.

Get Started Today

Download a free, 30-day trial of the CData JDBC Driver for PingOne to integrate with Dataiku, and effortlessly build custom AI/ML models from PingOne data.

Reach out to our Support Team if you have any questions.