Microsoft added variable libraries on April 1 to markedly improve the development pipeline experience, which greatly improves the entire CICD process for releasing content in Fabric. Now to make variable libraries work, parameters need to be implemented throughout pipelines, notebooks and semantic models. These parameters will be changed when items are moved using Development Pipelines. While development pipelines were originally created for Power BI using them to deploy Fabric content were problematic, but with Variable Pipelines, they are the best way to migrate code from dev to test to prod.
There are a few interesting exceptions that I want to highlight for creating and deploying your own semantic models. There are different processing issues that direct lake semantic models have that you will need to know if you want to implement a solution with them.
We will explore the foundational concepts of parameter usage in Fabric, demonstrating how to define, manage, and adjust parameters to for different environments. The session will highlight best practices for incorporating variable libraries, showcasing their role in facilitating seamless updates across multiple notebooks and pipelines.
Attendees will gain insights into:
• The architecture and benefits of using parameters in Fabric environments.
• Step-by-step guidance on setting up and utilizing variable libraries.
• Real-world examples illustrating the impact of parameterization on workflow efficiency.
By the end of this talk, participants will be equipped with the knowledge and tools to enhance their data engineering practices, leveraging the full potential of parameters and variable libraries in Fabric to drive more efficient and scalable data solutions.