Build AI/ML Models with Live Greenhouse 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 Greenhouse, Dataiku enhances data integration, preparation, real-time analysis, and reliable model deployment for Greenhouse data.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Greenhouse data. When you issue complex SQL queries to Greenhouse, the driver pushes supported SQL operations, like filters and aggregations, directly to Greenhouse 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 Greenhouse data using native data types.

This article shows how you can easily integrate to Greenhouse using CData JDBC Driver for Greenhouse 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 Greenhouse data. Be sure to install Dataiku DSS (On-Prem version) for your preferred operating system, beforehand.

Install the CData JDBC Driver for Greenhouse

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

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)
2. Click on Navigate to other sections of Dataiku menu on the top right section of the platform and select Administration.
3. Select the Connections tab.
4. In Connections, click on New Connections button.
5. Now, scroll down and select Other SQL databases.

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

   You need an API key to connect to Greenhouse. To create an API key, follow the steps below:

   1. Click the Configure icon in the navigation bar and locate Dev Center on the left.
   2. Select API Credential Management.
   3. Click Create New API Key.
   • Set "API Type" to Harvest.
   • Set "Partner" to custom.
   • Optionally, provide a description.
   4. Proceed to Manage permissions and select the appropriate permissions based on the resources you want to access through the driver.
   5. Copy the created key and set APIKey to that value.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.greenhouse.jar

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

   A typical JDBC URL is given below:

   jdbc:greenhouse:APIKey=YourAPIKey;
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.greenhouse.GreenhouseDriver
   • 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

   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.
9. Select any table from the list and click Preview to view the table data. Click Close to exit the window.

Creating a new project

To prepare data flows, create dashboards, analyze the Greenhouse 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.
2. In the Projects screen, click New Project and select + Blank Project.
3. In the New Project window, assign a Name and Project Key. Click Create. The new project dashboard opens up.
4. Select Notebooks from the menu at the top of the project screen.
5. Click on + Create Your First Notebook dropdown menu and select Write your own option.
6. In the New Notebook window, select SQL.
7. Now, select the required connection from the Connection dropdown and enter a name in the Notebook Name field.

Testing the connection

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

Get Started Today

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

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