How to build a Palantir Workflow

Building a comprehensive workflow in Palantir Foundry involves integrating several key components: Foundry, AIP (Artificial Intelligence Platform), Ontology, Workbooks, Workshops, and Actions. Below is a step-by-step guide to creating such a workflow, including code examples and actions.

1. Define the Ontology

The Ontology in Foundry serves as a semantic layer that standardizes data definitions across the platform.

• Create an Ontology Object: Define the structure and relationships of your data entities.

2. Develop Data Transformations

Use Foundry's code repositories to write data transformations that process raw data into structured formats.

• Python Transform: Process raw data and output a DataFrame.

3. Create a Workbook

Workbooks allow users to interact with data through a spreadsheet-like interface.

• Define a Workbook: Create a workbook that references your processed data.

4. Build an Application with Workshop

Workshop enables the creation of interactive applications within Foundry.

• Create a Workshop Application: Develop an application that utilizes your workbook.

5. Implement Actions

Actions automate tasks within Foundry, such as data processing or model training.

• Define an Action: Create an action that triggers a data transformation.

6. Deploy the Workflow

Deploy your workflow to make it operational.

• Deploy Components: Use Foundry's deployment tools to deploy your Ontology, transforms, workbooks, and applications.

7. Monitor and Iterate

After deployment, monitor the workflow's performance and make necessary adjustments.

• Monitor Logs: Use Foundry's logging tools to track the execution of your workflow.

For more detailed tutorials and code examples, refer to Palantir's official documentation and training resources.

By following these steps, you can build a robust workflow in Palantir Foundry that integrates data processing, interactive applications, and automation.

Sources

learn.palantir.com