Analysts working in Looker often hit a wall when metrics look wrong, fields go missing, or dashboards behave unexpectedly—issues that originate in the data model, not the query.

In this course, Introduction to Data Modeling with LookML, you'll gain the ability to understand, build, and troubleshoot the LookML layer that powers every Explore.

First, you'll explore what LookML is, how it fits into the Looker ecosystem, and how modeling decisions directly affect analyst workflows.

Next, you'll discover how to model Explore joins that combine datasets safely while preserving metric accuracy. Then, you'll see how to create dimensions for common analysis needs, including time-based fields and segmentation buckets.

Finally, you'll learn how to create reliable, reusable measures with proper formatting, filters, and testing. When you're finished with this course, you'll have the skills and knowledge of LookML data modeling needed to read and modify a Looker data model, diagnose common data issues, and contribute meaningfully to your organization's analytics layer.

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