# Hands-On Tutorial: Data Pipelines[¶](https://knowledge.dataiku.com/latest/courses/advanced-data-prep/data-pipelines/introduction.html#hands-on-tutorial-data-pipelines "Permalink to this headline")

If you have learned how to manipulate data in the Basics courses, you’re ready to build a more complex data pipeline.

This tutorial introduces two fundamental Dataiku concepts:

* the difference between recursive and non-recursive dataset build options

* how to propagate schema changes downstream in a Flow.

## Prerequisites[¶](https://knowledge.dataiku.com/latest/courses/advanced-data-prep/data-pipelines/introduction.html#prerequisites "Permalink to this headline")

This tutorial assumes that you have completed the Basics courses prior to beginning this one!

## Create the Project[¶](https://knowledge.dataiku.com/latest/courses/advanced-data-prep/data-pipelines/introduction.html#create-the-project "Permalink to this headline")

From the Dataiku homepage, click **+New Project > DSS Tutorials > General Topics > Tutorial: Data Pipelines**.

Note

You can also download the starter project from this website and import it as a zip file.

In this tutorial, we are going to practice building the Flow in different ways, and so let’s start by clearing all of the datasets except for the two uploaded input datasets.

* Select the four downstream datasets (*orders\_prepared*, *orders\_by\_customer*, *customers\_orders\_joined*, *customers\_labelled*).

* From the Actions sidebar, choose **Clear data**.
