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4 ways to build dbt Python models | Datafold

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dbt has become the leading data transformation tool in the Modern Data Stack. With its comprehensive suite of features, including development, testing, and documentation, dbt serves as a central hub for all your data transformation needs. Although dbt is written in Python, it was originally built to allow only SQL for data transformations. However, as a trend toward convergence amongst various DW vendors rises, in terms of the languages and capabilities of the platforms, dbt Labs worked hard to allow the usage of Python in dbt models. So, do you feel SQL is a constraint to your transformation process in dbt? Do you want to run complex queries that can not be done by SQL only? Do you want to apply machine learning techniques in your transformation? What if you could have all this transformation logic within your dbt DAG? The wait is over, Python support for dbt is finally here and it's causing quite a buzz in the data community. In this article, we'll first cover the use cases where Pyt

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