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Watch On-Demand: Dynamic Data Modeling Workshop

Dynamic Data Modeling in Cube with Python and Jinja

Now you can use Python to configure Cube programmatically; moreover, you can also use Python and Jinja to define dynamic data models, reuse code, and simplify your day-to-day data modeling tasks with Cube.

It means that you can have a Python-only experience with Cube, either providing programmatic configuration or authoring dynamic data models with YAML and Jinja. You can read more about that in the following blog posts:

In this workshop, see a deep dive into Python and Jinja with Cube. We’ll start by discussing the common cases for programmatic configuration and dynamic data models, review the code structure and syntax for Python and Jinja, and explore more with live demos.

Watch On-Demand: here to view at any time.