Ctrl+Data: Fabric’s Blueprint for Parameterization
Proposed session for SQLBits 2026TL; DR
Join us for a demo-heavy presentation about Fabrics Variable Library and how it can improve your workflows in data pipelines, notebooks and other fabric items.
Session Details
Discover how to combine the new parameterizable connections with Fabrics SQL Databases to build platform-native, metadata-driven Data Pipelines, Notebooks and more!. This approach enhances reusability and reduces the number of artifacts that require maintenance. By separating code from configuration, you can additionally increase operational efficiency.
This session will show you the possibilities that these features offer, providing you with practical examples and insights. Additionally, you’ll benefit from expert guidance on best practices for designing parameterized pipelines, ensuring that you create systems that are not only powerful but also scalable and adaptable to evolving data needs. Join us to elevate your data workflows and harness the expertise needed to implement robust pipeline architectures.
This session will show you the possibilities that these features offer, providing you with practical examples and insights. Additionally, you’ll benefit from expert guidance on best practices for designing parameterized pipelines, ensuring that you create systems that are not only powerful but also scalable and adaptable to evolving data needs. Join us to elevate your data workflows and harness the expertise needed to implement robust pipeline architectures.
3 things you'll get out of this session
Understand the structure and usecases of the variable library
integration in data pipelines
integration in notebooks
Speakers
Tim Spannagel's other proposed sessions for 2026
AI in Action: Navigating Microsoft Fabric with Data Agents and Copilots - 2026
From Dev to Dashboard – Azure SQL vs Fabric SQL in Practice - 2026
SAP to Fabric: A Step‑by‑Step Integration Playbook for S/4HANA & ECC - 2026
Code, Commit, Conquer: Tips & Tricks for your daily workflow - 2026
Mirror, mirror on the wall, load my data! load it all! - 2026