Managing and Optimizing Semantic Model Refreshes

Data Ingestion and Semantic Models with Microsoft Fabric

Alex Kuntz

Head of Cloud Curriculum, DataCamp

Data Refresh in Semantic Models

What is Data Refresh?

  • Ensures latest data is visible in reports

Refresh Requirements for Storage Modes:

  • Import Mode: Requires scheduled refresh for updates
  • DirectQuery Mode: No refresh needed; queries live data
  • Direct Lake Mode: No refresh needed; accesses OneLake directly

Data Refresh in Semantic Model

Data Ingestion and Semantic Models with Microsoft Fabric

Scheduled and On-Demand Refresh

  • Scheduled Refresh

    • Automates refresh at specific intervals
    • Ideal for regular updates without manual effort

  • On-Demand Refresh

    • Manually triggers refresh anytime
    • Flexibility for immediate updates
    • Useful for real-time scenarios

Semantic Model Refresh Options

Data Ingestion and Semantic Models with Microsoft Fabric

Incremental and Full Refresh

Incremental Refresh

  • Refreshes only new or modified data
  • Reduces time and resource usage
  • Ideal for large datasets with regular updates

Full Refresh

  • Reloads the entire dataset
  • Ensures complete data consistency
  • Suited for smaller datasets or full data replacement scenarios

Data Refresh in Semantic Model - Incremental

Data Refresh in Semantic Model - Incremental

Data Ingestion and Semantic Models with Microsoft Fabric

Semantic model refresh activity

  • Automates dataset refreshes to keep Power BI reports up-to-date.
  • Integrated within Microsoft Fabric's Data Factory.

Semantic Model Refresh Activity

Key Features:

  • Connection: Requires a pre-configured connection to Power BI datasets.
  • Default Behavior: Runs a full data refresh by default, replacing all data.
  • Preview Feature: Currently available in preview, enabling early access to try it out
Data Ingestion and Semantic Models with Microsoft Fabric

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Data Ingestion and Semantic Models with Microsoft Fabric

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