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Workloads-Specific/DataWarehouse/BestPractices.md

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@@ -50,7 +50,7 @@ Create a warehouse solution that segments data as follows:
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- Silver Layer: Applies data cleansing, validation, and enrichment.
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- Gold Layer: Produces analytics-ready data using optimized storage formats like Parquet or Delta Lake, with partitioning by date or region. Integrate metadata catalogs and RBAC controls for added governance.
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> Here is a [reference of a medallion architecture using only Fabric](./Workloads-Specific/DataWarehouse/Medallion_Archuitecture/). If you need to handle `complex data transformations and large-scale data processing`, you can use our combined solution of **Fabric + Databricks**. This powerful combination leverages the strengths of both platforms to provide a robust data processing pipeline. This workshop on [Fabric with Databricks for Data Analytics](https://microsoft.github.io/TechExcel-Fabric-with-Databricks-for-Data-Analytics/) offers a comprehensive step-by-step guide on developing Medallion Architecture using Fabric and Databricks. <br/>
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> Here is a [reference of a medallion architecture using only Fabric](./Workloads-Specific/DataWarehouse/Medallion_Architecture/). If you need to handle `complex data transformations and large-scale data processing`, you can use our combined solution of **Fabric + Databricks**. This powerful combination leverages the strengths of both platforms to provide a robust data processing pipeline. This workshop on [Fabric with Databricks for Data Analytics](https://microsoft.github.io/TechExcel-Fabric-with-Databricks-for-Data-Analytics/) offers a comprehensive step-by-step guide on developing Medallion Architecture using Fabric and Databricks. <br/>
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| Medallion Architecture using only Fabric | Medallion Architecture Fabric + Databricks |
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| --- | --- |

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