22-25 April 2026 
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SQLBits 2026
Everything you need to know about Pure Python notebooks in Fabric
Discover how to leverage pure Python notebooks in Microsoft Fabric for modern data engineering and analytics. Learn best practices, integration patterns, performance optimization, and when to use Python over SQL in your Fabric workflows.
Everything you need to know about Pure Python notebooks in Fabric
Discover the power of Python notebooks in Microsoft Fabric and learn how they're transforming data engineering and analytics workflows. This session provides a comprehensive guide to leveraging pure Python notebooks within the Fabric ecosystem, moving beyond traditional SQL-based approaches.
We'll explore the core capabilities of Python notebooks in Fabric, including seamless integration with data lakes, real-time data processing, and advanced analytics. You'll learn best practices for structuring your notebooks, managing dependencies, and optimizing performance for large-scale data operations.
Key topics include:
Setting up and configuring Python notebooks in your Fabric workspace
Working with Fabric's native Python libraries and APIs
Data ingestion patterns and connecting to multiple data sources
Building reusable functions and modules for production workflows
Debugging techniques and common pitfalls to avoid
Discover the power of Python notebooks in Microsoft Fabric and learn how they're transforming data engineering and analytics workflows. This session provides a comprehensive guide to leveraging pure Python notebooks within the Fabric ecosystem, moving beyond traditional SQL-based approaches.
We'll explore the core capabilities of Python notebooks in Fabric, including seamless integration with data lakes, real-time data processing, and advanced analytics. You'll learn best practices for structuring your notebooks, managing dependencies, and optimizing performance for large-scale data operations.
Key topics include:
Setting up and configuring Python notebooks in your Fabric workspace
Working with Fabric's native Python libraries and APIs
Data ingestion patterns and connecting to multiple data sources
Building reusable functions and modules for production workflows
Debugging techniques and common pitfalls to avoid