Deep dive into using notebooks with your semantic model (Preview)
We are excited to introduce one-click experiences that make it easier than ever to start using Fabric notebooks and semantic link to analyze your semantic models on the web!
Fabric Notebooks
Microsoft Fabric Notebooks offer an interactive solution for data engineers and data scientists to build Apache Spark jobs, manage data workflows, and develop machine learning models. They feature an easy-to-use, low-code interface with enterprise security, integration with Lakehouse, and built-in visualization tools. The notebooks also support collaboration through commenting, tagging, and version control, simplifying the management of code execution, data exploration, and model deployment.
Semantic Link
Semantic link is a feature that allows you to establish a connection between semantic models and data science capabilities in Microsoft Fabric. This lets you optimize Fabric items for performance, memory, and cost.
Out-of-the-Box Experiences for Your Semantic Models
Simply choose one of our pre-configured notebooks, and we’ll handle the creation and configuration, allowing you to seamlessly run analysis against your semantic model.
We are offering the following out-of-the-box experiences for your semantic models:
Best Practices Analyzer – When you run this notebook, the Best Practice Analyzer (BPA) will offer tips to improve the design and performance of your semantic model. By default, the BPA checks a set of 60+ rules against your semantic model and summarizes the results. These rules come from experts within Microsoft and the Fabric Community. You’ll get suggestions for improvement in five categories: Performance, DAX Expressions, Error Prevention, Maintenance, and Formatting.
Community
Using notebooks and semantic link with your Power BI semantic models allows the Power BI community to create notebooks that connect to semantic models for rich analysis and augmentation. The support of these pre-configured notebooks is thanks to years of amazing contributions across our Microsoft and Power BI communities. We especially would like to thank the following individuals:
- Daniel Otykier for his ongoing contributions creating Best Practice Analyzer in Tabular Editor.
- Marco Russo for his ongoing contributions creating VertiPaq Analyzer.
- Michael Kovalsky for his ongoing contributions creating semantic link labs, which serve as the foundation for these pre-configured notebooks.
The Power BI product group is deeply grateful to Daniel, Marco, and Michael for all their work developing these rich tools! We are excited for more people across the Power BI and Fabric communities to follow in their footsteps and develop even more notebooks that use semantic link to analyze and augment Power BI semantic models and reports. We believe there is so much potential with these powerful capabilities, and we are so excited to see what all the community continues to develop in this space!
Power BI Community Notebooks Gallery
To help the community share all the Power BI notebooks you create we are excited to announce the Power BI Community notebooks gallery! Here you can explore and submit notebooks you’ve created to enhance your Power BI data analysis and reporting with the rest of the Power BI community.
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