Palantir Foundry Pipelines And Dataset Bootcamp

Master Foundry pipelines with data import, transforms, QA checks, scheduling, and dataset output.

What you’ll learn
Learn the Foundry Pipelines interface, core concepts, and workflow so you can navigate confidently and prepare to build your first pipeline.
Learn how to import, connect to, and upload raw data from multiple sources so you can reliably bring datasets into Foundry.
Learn to clean, add to, split, merge, test and validate data using Foundry transforms so you can build clear, maintainable pipelines.
Learn to publish datasets, set write modes, schedule builds, run tests, and prepare data for reliable downstream use.

Requirements
No programming experience is needed. To get the most from this course, it would help if you have access to Foundry, so you can practise key concepts. You must be comfortable working with websites and data, such as spreadsheets.

Description
Building reliable, well-structured data pipelines is at the heart of working effectively in Palantir Foundry. In this hands-on course, you’ll learn how to take raw data from a variety of sources, transform it with confidence, and publish clean, trustworthy datasets that are ready for real-world use.We begin by exploring the Foundry Pipelines interface so you can navigate with ease and understand how pipelines, datasets, and transforms fit together. You’ll learn how to import data from within Foundry, upload private files, and onboard publicly available datasets, giving you a solid foundation for working with different types of inputs.From there, we dive into transforming your data. You’ll work with JSON and geoJSON, troubleshoot extraction issues, reshape data using splits and static columns, combine logic with Regex and conditional expressions, and enrich your pipelines with joins, unions, and built-in functions. Along the way, you’ll develop a strong mental model of how schemas evolve and how transforms chain together.Next, you’ll learn how to load and operationalise your work. We cover write modes, scheduling, error handling, data expectations, and unit tests so you can ensure quality before publishing. You’ll also learn how to improve dataset usability by adding metadata, managing access, and applying best-practice governance.Finally, we touch on branching to help you develop changes safely in a controlled environment.By the end of this course, you’ll be able to confidently build, test, and publish complete data pipelines in Foundry, collaborating with colleagues along the way.

This course is designed for analysts, data engineers, and anyone working with Foundry who wants to learn how to build, transform, and publish data pipelines confidently.

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