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Over the last two weeks, we've walked through how to create a foundational star schema data model using a tool like dbt.

We covered how to create Dimensions and Facts to make up the core model.

But creating the tables alone is just the first step.

Because as we know...data and custom logic is rarely ever 100% perfect.

Which is why having processes to test the quality of the data is incredibly important as well.

Fortunately, dbt provides some great built-in functionality to help address this scenario with just a few simple configurations.

And without needing to overcomplicate things early on.

So in this video, which is the last of this 3-part mini series, you'll see how we can put a bow around our initial data model by adding some baseline data quality tests.

Enjoy.

00:00 Intro
00:47 Using Built-in Tests
01:44 Adding YML Files
03:22 Review Compiled SQL
04:02 Using dbt Build
04:28 Test Failures
05:04 Committing the Changes