In recent years, Medallion architecture has become one of the leading logical frameworks for storing and organizing data in modern data platforms. By applying Medallion architecture in Microsoft Fabric, organizations can build data pipelines that are not only scalable and adaptable but also deliver high-quality results. This setup can support analytics, reporting, and machine learning.
Let’s explore the core concepts of Medallion architecture, the bronze-silver-gold layers, and practical recommendations on how to implement this architecture effectively. You’ll also learn how Microsoft Fabric lakehouse and warehouse align with Medallion concepts.
Table of Contents
What Is Medallion Architecture?
Medallion architecture is a layered approach to organizing data in stages of increasing quality and usability. You may have heard the terms bronze, silver, and gold layers, and in some cases, even platinum. Each stage improves the previous one, ensuring data moves from raw ingestion to trusted, business-ready insights.
Applying Medallion architecture in Microsoft Fabric can be powerful because it integrates with tools such as OneLake, Lakehouse, Data Warehouses, SQL databases, and pipelines. Whether you’re building a lakehouse, enabling real-time analytics, or preparing a platform, the Medallion model ensures your data evolves in a structured and reliable way.
Why Use Medallion Architecture in Microsoft Fabric?
Before diving into the layers, let’s answer the big question: why adopt this approach in Microsoft Fabric?
- Consistency: All data follows a predictable flow from raw to refined.
- Flexibility: You can start small (for example, with a lakehouse) and expand to other technologies as your use cases grow.
- Scalability: With Microsoft Fabric, you can handle multiple data sources (databases, APIs, IoT sensors, or files) without locking into one rigid path.
- Data Quality: Each layer enforces cleansing, validation, and enrichment, ensuring insights are trustworthy.
The Bronze Layer: Raw Data
The bronze layer is where raw data first lands inside Microsoft Fabric. Think of it as your “landing zone.” Here, the information is ingested from diverse sources, such as:
- Relational databases (SQL Server, Oracle, etc.)
- Flat files (CSV, Excel, JSON)
- APIs exposed by SaaS providers
- IoT and real-time data streams
In most cases, the bronze layer stores data exactly as it was in the source system. However, minor transformations may be applied if necessary, like restructuring JSON responses.
In Fabric, the Lakehouse is often the preferred choice for the bronze layer because it supports both structured and semi-structured data. Warehouses or SQL databases can also be used, depending on your team’s needs and the type of source data.
Tip: Consider using both a transient staging area (for temporary daily loads) and a persistent staging area (for long-term raw copies). This provides flexibility for data modeling and troubleshooting.
The Silver Layer: Cleansed and Enriched Data
Once data is staged, it moves into the silver layer. This is where quality and usability take center stage.
In this layer, you can:
- Apply cleansing rules and validation
- Standardize data types and formats
- Enrich datasets with business rules
- Create dimensions and fact tables for reporting
- Optionally, model data using the Data Vault methodology
For transformations, Microsoft Fabric offers multiple paths. With Lakehouse, you can use Spark notebooks and pipelines to manage complex transformations. With a Data Warehouse, you can lean on T-SQL for processing and modeling.
Design Consideration: If you use Lakehouse for the bronze layer, it’s often simpler to continue with Lakehouse in silver. However, organizations preferring SQL-based approaches may opt for the warehouse instead.
The Gold Layer: Business-Ready Insights
Finally, data reaches the gold layer, which is designed for business consumption.
Here, the focus shifts to:
- Aggregations and summarizations
- Organizing data by business domains
- Optimizing performance for reporting tools
- Making datasets easily accessible to Power BI, SQL analytics endpoints, and applications
By the time data arrives at the gold stage, it’s clean, enriched, and structured for decision-making. As a result, it ensures business users don’t have to wade through billions of rows but instead work with concise, actionable insights.
For example, instead of exposing a 50-trillion-row transactions table, you might provide a summarized dataset showing daily sales by region, which is ready for dashboards and executive reports.
Medallion Architecture in Microsoft Fabric: Silver and Gold Layers Explained
Now, let’s dig deeper into the role of Medallion architecture in Microsoft Fabric.
The Silver Layer in Medallion Architecture
Within the silver layer, lakehouses play a pivotal role. Every time you deploy a lakehouse, it automatically provisions a SQL analytics endpoint. This endpoint functions much like a SQL Server connection string, allowing you to query data in a way that you’re used to. Along with it, Fabric generates a Power BI dataset using Direct Lake, which directly connects to OneLake storage for high-performance analysis.
Limitations
- SQL endpoints only support read operations, which means you cannot update or delete data.
- You can create objects such as views or stored procedures, but they must remain read-only.
- Direct Lake datasets currently do not support Visual Studio, which may affect development workflows.
Despite these constraints, the combination of lakehouse, SQL endpoint, and Direct Lake dataset provides powerful options for building the silver layer. You can also choose to use warehouses instead, especially if you prefer SQL-based transformations or need stored procedure support. Both approaches align with medallion architecture, and the choice depends mainly on team skills and project requirements.
As you move from the bronze to the silver layer, you can take advantage of shortcuts that help skip unnecessary data transfers. This kind of flexibility is one of the reasons Microsoft Fabric works so well for organizations juggling data from many different sources.
The Gold Layer in Medallion Architecture
The gold layer in Medallion architecture in Microsoft Fabric focuses on aggregation and business-ready insights. Rather than moving or duplicating data, you can simply leverage the assets already created in the silver layer.
For example, fact tables and dimensions defined in the silver layer can be surfaced through shared semantic models in Power BI. These models centralize KPIs, calculations, and business rules. Depending on organizational needs, you might create domain-specific datasets (finance, HR, operations) or aim for a single corporate semantic model with row-level and column-level security applied.
Aggregations are another critical aspect. Instead of exposing trillions of rows directly to reports, you can create SQL views within the lakehouse or warehouse to summarize data before presenting it. Although SQL endpoints do not yet support Direct Lake for aggregations, they remain highly effective for reducing complexity and optimizing performance.
Real-World Variations of Medallion Architecture in Microsoft Fabric
In practice, Medallion architecture is rarely applied rigidly. For instance, while the ideal flow is bronze → silver → gold, some organizations load reference or master data directly into the silver layer without passing through the bronze layer. Similarly, operational reporting sometimes pulls directly from the bronze layer when speed is more important than transformation.
Other real-world patterns include:
- Lakehouse-only implementations for bronze and silver layers.
- Warehouse-only designs that lean on proven SQL technologies.
- Hybrid approaches combining lakehouses and warehouses, depending on workload.
- Simplified pipelines where reporting happens directly from a bronze-layer lakehouse dataset.
Each design has trade-offs, and the right choice depends on scale, data types, and business priorities.
Medallion Architecture in Microsoft Fabric: Workspace Recommendations
When setting up workspaces in Microsoft Fabric, developer experience is a key consideration. Although the ideal design is to separate bronze, silver, and gold lakehouses into different workspaces, cross-workspace queries can be challenging today. Therefore, it is often more practical to keep bronze and silver lakehouses in the same workspace for smoother notebook operations.
At the gold layer, however, it’s best practice to separate semantic models into their own workspace. This separation ensures clean governance and allows reports to connect consistently to curated datasets. A strategic setup might include:
- One workspace for data storage (bronze/silver lakehouses).
- Another for semantic models.
- A dedicated workspace for reports.
- Optional workspaces for machine learning or integration processes.
This layered workspace strategy keeps data management organized while reducing maintenance complexity.
Final Thoughts
Implementing Medallion architecture in Microsoft Fabric provides structure, scalability, and consistency for data management. Start simple and adapt based on your organization’s needs. Whether you choose lakehouses, warehouses, or a hybrid, the key is to avoid overcomplicating things at the start.
Ultimately, Medallion architecture is a logical framework, not a rigid rulebook. By understanding the trade-offs of each approach, you can design a Fabric-based architecture that balances performance, flexibility, and maintainability.
If you want to learn more about data architecture, explore our Data Architecture expertise to help build smarter and more efficient systems.
Frequently Asked Questions
Question: Do I always need all three layers (bronze, silver, gold) for Medallion architecture in Microsoft Fabric?
Answer: Not always. While the full three-layer design is common, some organizations skip bronze for reference or master data or even report directly from silver. The framework is flexible and should be adapted to business needs.
Question: Can I use both lakehouses and warehouses in Medallion architecture?
Answer: Yes. Lakehouses are often used for raw and semi-structured data, while warehouses are ideal for SQL-based transformations. Many organizations use a hybrid approach, combining both depending on team skills and workload requirements.
Question: How should workspaces be structured in Microsoft Fabric for Medallion architecture?
Answer: Best practice is to separate workspaces by purpose. For example, one workspace for bronze/silver storage, another for semantic models, and another for reports. This improves governance and keeps the architecture organized.
