9 - Key Takeaways

Adding Data Expectations to your pipeline management practice gives you more granular control over health checks and the ability to prevent unexpected data from propagating to downstream resources. And since these checks are defined in your Git-backed repository, they’re subject to more rigorous change management than your standard Data Health checks.

In this tutorial you:

1. Added a primary key check to your flight_alerts_clean data transform.
2. Added a column expectation (is_in) in your flight_alerts_clean transform code.
3. Added a group-by expectation (is_unique) in your flight_alerts_joined_passengers transform code.
4. Added a schema expectation check on your flight_alerts_by_country transform generator code.

Below is a list of product documentation used in the course of this training:

• Data Expectations Overview
• Data Expectations Quick Start
• Data Expectations Reference

The next tutorial will introduce you to the Foundry Ontology and guide you through the process of generating optimal datasets to support operational workflows the Ontology enables.