SQL and Jinja for dbt
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 43m | 117 MB
Instructor: Pinal Dave
This course teaches query optimization, Jinja templating, and macros to automate SQL workflows, making your data models efficient, scalable, and maintainable.
What you'll learn
Enhancing dbt workflows leads to efficient and maintainable data models.
In this course, SQL and Jinja for dbt, you'll gain the ability to write optimized dbt models, automate transformations, and apply Jinja scripting for dynamic data references.
First, you'll explore best practices for writing efficient SQL in dbt models.
Next, you'll discover how to enhance dbt transformations using Jinja templating for dynamic schema and table references.
Finally, you'll learn how to automate SQL workflows using dbt macros, enabling code reusability, logic-driven queries, and debugging strategies.
When you're finished with this course, you'll have the skills and knowledge to optimize dbt models, streamline SQL workflows, and apply Jinja-based automation for scalable data transformations.
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