Forum Discussion
Single Version of Truth Mapping for Multiple Data Using a Single Notebook
Hello Mirdula
not official MS recommendations, but these are few which I try to follow in my deployments
Centralize SVOT Logic: Keep your mapping logic modular and in shared modules to avoid duplication.
• Parameterize Notebooks: Use parameters for dataset type, source/target paths, and configuration settings.
• Handle Function-Specific Needs: Apply conditional logic or configuration-driven mappings for each functional dataset (e.g., Finance, Sales).
• Orchestrate with Pipelines: Use Microsoft Fabric pipelines or notebook widgets to pass parameters and manage execution.
• Follow Medallion Architecture: Structure your data into Bronze (raw), Silver (SVOT-mapped), and Gold (curated) layers.
• Prioritize Maintainability: Use the DRY (Don’t Repeat Yourself) principle so updates are easy and consistent across datasets.
Hello Mirdula
not official MS recommendations, but these are few which I try to follow in my deployments
Centralize SVOT Logic: Keep your mapping logic modular and in shared modules to avoid duplication.
• Parameterize Notebooks: Use parameters for dataset type, source/target paths, and configuration settings.
• Handle Function-Specific Needs: Apply conditional logic or configuration-driven mappings for each functional dataset (e.g., Finance, Sales).
• Orchestrate with Pipelines: Use Microsoft Fabric pipelines or notebook widgets to pass parameters and manage execution.
• Follow Medallion Architecture: Structure your data into Bronze (raw), Silver (SVOT-mapped), and Gold (curated) layers.
• Prioritize Maintainability: Use the DRY (Don’t Repeat Yourself) principle so updates are easy and consistent across datasets.
Thank you for your response nilendraFabric 🙂 . It helps 👍
