Handling incremental refresh during migration: Best practices for semantic model conversion and data reloads

Smoothly manage incremental refresh and data reloads during your Power BI to Microsoft Fabric migration

Migrating from Microsoft Power BI to Microsoft Fabric offers several advantages but also introduces challenges, especially with incremental refresh in Power BI datasets. This feature updates large datasets by refreshing only recent data, but it doesn’t seamlessly translate into Fabric’s architecture. Organizations planning the migration must understand how to handle these datasets to avoid disruptions. This post covers the challenges of incremental refresh during migration and offers best practices for a smooth transition to Microsoft Fabric. 

Challenges with incremental refresh during migration 

Power BI uses incremental refresh to update a subset of data, making it efficient for large datasets. However, Microsoft Fabric handles data differently. The migration process often requires a full data reload—meaning all data, not just incremental updates, must be refreshed. 

Key challenges 

• Semantic Model Conversion: Incremental refresh configurations in Power BI don’t automatically translate into Fabric’s semantic models 

• Full Reload Requirement: Fabric doesn’t fully support incremental refresh from Power BI, requiring a complete data refresh and reloading of models from scratch 

These challenges can delay the migration and impact production environments, particularly in fast-paced data operations. 

Best practices for migrating incremental refresh datasets 

To ensure a smooth migration, follow these best practices: 

Expect full data reloads 

A full data reload is often necessary when migrating Power BI datasets with incremental refresh. Set realistic expectations about the time and resources required. 

Action: Acknowledge the need for a full refresh and plan accordingly. 

Best practice: Ensure PBIX source files are organized and accessible to avoid delays when republishing models. 

Maintain and organize PBIX source files 

You’ll need access to original PBIX files for republishing. Disorganized files can cause errors and delays. 

Action: Keep a structured repository of PBIX files with version control. 

Best practice: Document each PBIX file’s data refresh configuration to ensure settings are replicated in Fabric.  

Test migration with sample datasets 

Test migration with a small, non-critical dataset before scaling up. This helps identify issues in semantic models and incremental refresh configurations. 

Action: Use sample datasets to validate migration and confirm proper configuration. 

Best practice: Run performance benchmarks on the migrated model to identify discrepancies or performance degradation. 

Leverage Fabric’s semantic model features 

Fabric introduces new features for managing semantic models and data refreshes. Rework models to optimize performance in Fabric’s environment. 

Action: Explore Fabric’s semantic model and Lakehouse features. 

Best practice: Use Fabric’s tools to streamline your data pipeline and refresh processes post-migration. 

On a concluding note 

Migrating Power BI datasets with incremental refresh to Microsoft Fabric requires careful planning. The main challenges—semantic model conversion and full data reloads—can be managed with the right approach. By setting expectations, organizing assets, testing with sample datasets, and using Fabric’s features, you can ensure a smooth transition to Microsoft Fabric’s robust analytics capabilities