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Organizations often face challenges when trying to scale analytics across large volumes of data stored in centralized SQL databases. As business teams demand faster, more tailored insights, traditional reporting pipelines can become bottlenecks. By adopting Lakehouse architecture with Microsoft Fabric, business groups can mirror their SQL data into OneLake and organize it using the Medallion architecture—Bronze, Silver, and Gold layers. Materialized lake views play a crucial role in this setup, enabling automated, declarative transformations that clean and enrich data in the Silver layer. This empowers teams to build reliable dashboards and AI-driven insights on top of curated data, all while maintaining performance, governance, and security on a scale.
In this post, we will cover how enterprises can use materialized lake views to streamline data orchestration and enhance data quality, monitoring across silver and gold layers, while mirroring their SQL DB tables to Fabric in the Bronze layer.
Mastering_Declarative_Data_Transformations_with_Materialized_Lake_Views
Step 1: Mirror your Azure SQL database to Fabric using this tutorial into your desired Workspace (Workspace A)
Step 2: Create a shortcut from the Bronze Tables (with filters required) into your Workspace (Workspace B)
Step 3: Build Silver and Gold materialized lake views, with required filters applied on the bronze layer, by using the MLV syntax in your notebook.
Mastering_Declarative_Data_Transformations_with_Materialized_Lake_Views
Step 4: Once your Silver and Gold materialized lake views are completed, navigate to the Lakehouse where you have built your Silver and Gold Materialized Lake views, you can navigate to the 'Manage materialized lake views' pane to view the lineage.
Mastering_Declarative_Data_Transformations_with_Materialized_Lake_Views
Step 5: Continue on to schedule the materialized lake view runs as per your business needs.
Mastering_Declarative_Data_Transformations_with_Materialized_Lake_Views
With these steps you can continue to bring in your SQL Server data into Fabric, and materialize them in your Lakehouse, while turning the transactional data into insights using Fabric materialized lake views.
Refer to the Materialized Lake Views documentation.
Stay tuned for updates and feature enhancements in materialized lake views, including viewing the bronze layer leaf nodes across Workspace / Lakehouse in your lineage.
Provide your feedback and suggest ideas via Fabric Ideas.
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