In the world of Power BI, Microsoft Fabric, and modern data engineering, few architectural patterns are discussed more than the Medallion Architecture. The familiar Bronze, Silver, and Gold layering approach has become a standard recommendation for many data teams.
But here’s the real question:
Do you actually need a Silver layer?
That debate recently sparked a passionate discussion between Patrick and Marthe, two experienced data professionals with very different perspectives on architecture, scalability, and governance.
And honestly? Both sides make excellent points.
In this article, we’ll break down:
- What Medallion Architecture actually is
- The purpose of Bronze, Silver, and Gold layers
- Why some teams overbuild their architectures
- When a Silver layer adds real value
- When you should skip it entirely
- Best practices for Power BI and Microsoft Fabric implementations
If you’re designing a data platform in Power BI or Fabric, this discussion could save your team significant complexity, maintenance, and technical debt.
What Is Medallion Architecture?
Medallion Architecture is a layered data design pattern commonly used in:
- Microsoft Fabric
- Azure Databricks
- Lakehouse architectures
- Modern data warehouses
The architecture typically includes three layers:
Bronze Layer (Raw Data)
The Bronze layer stores raw, unprocessed data exactly as it arrives from source systems.
Characteristics:
- Minimal transformations
- Historical preservation
- Source-of-truth ingestion
- Append-heavy workloads
Examples:
- ERP exports
- CRM data
- API responses
- CSV files
- IoT streams
Silver Layer (Cleaned & Standardized Data)
The Silver layer is where data gets:
- Cleaned
- Validated
- Standardized
- Deduplicated
- Conformed across systems
This layer often includes:
- Standard naming conventions
- Data quality checks
- Null handling
- Common business rules
- Reusable transformation logic
Gold Layer (Business-Ready Data)
The Gold layer contains curated, business-facing datasets optimized for:
- Reporting
- Analytics
- Dashboards
- Power BI semantic models
- Executive KPIs
This is where business logic and domain-specific calculations are typically applied.
Patrick’s Argument: Most Teams Overbuild the Silver Layer
Patrick’s main point is simple:
“Most teams add a Silver layer without clearly defining its responsibility.”
And that’s an incredibly important architectural lesson.
Every Layer Creates Ownership Boundaries
Adding another layer doesn’t just add structure.
It adds:
- Maintenance
- Governance
- Operational overhead
- Responsibility boundaries
- Data handoffs
Patrick argues that many teams implement Bronze → Silver → Gold simply because it’s trendy or considered “best practice.”
But when asked:
- Who owns the Silver layer?
- What business responsibility does it enforce?
- Why does it exist?
…many teams don’t have good answers.
The Hidden Cost of Extra Layers
Every additional layer introduces:
- More pipelines
- More orchestration
- More storage
- More monitoring
- More troubleshooting
- More latency
And if the Silver layer is only performing lightweight transformations that could easily exist elsewhere, then the architecture may be unnecessarily complex.
This is especially true for:
- Small teams
- Simple reporting environments
- Stable source systems
- Limited use cases
In these situations, Bronze-to-Gold pipelines may be perfectly sufficient.
A Common Anti-Pattern in Data Engineering
Patrick highlights a common issue:
Many teams claim they have a “Silver layer,” but in reality they only have:
- Basic cleanup
- A few joins
- Minor transformations
- Temporary staging logic
That’s not necessarily a reusable standardization layer.
It may simply be:
- A staging area
- A processing checkpoint
- An unnecessary abstraction
And if it doesn’t provide reusable business value, then it may not deserve its own architectural tier.
Marthe’s Argument: Standardization Prevents Chaos
Marthe strongly disagrees with eliminating the Silver layer entirely — especially in larger enterprise environments.
And her reasoning is equally compelling.
Without Standardization, Logic Gets Duplicated Everywhere
Imagine transaction data flowing into your platform.
Now imagine:
- Finance needs reporting
- Sales needs analytics
- Operations needs monitoring
If each team independently:
- Renames columns
- Handles null values differently
- Applies inconsistent business rules
- Cleans data in separate pipelines
…you quickly create:
- Logic duplication
- Inconsistent metrics
- Conflicting reports
- Governance problems
This is exactly the type of chaos the Silver layer is designed to prevent.
The Silver Layer as a Reusable Foundation
Marthe views the Silver layer as a reusable building-block layer.
Instead of every business domain solving the same data quality issues repeatedly, the Silver layer centralizes:
- Standard naming conventions
- Shared transformation logic
- Data quality validation
- Schema consistency
- Common enrichment processes
This creates:
- Reusability
- Scalability
- Consistency
- Easier governance
And in enterprise environments with multiple business domains, that standardization becomes critical.
The Real Answer: It Depends on Complexity
Interestingly, both Patrick and Marthe eventually agree on the most important point:
Architecture is not about layers. It’s about responsibilities.
That’s the key takeaway.
The question is not:
- “Should every project use Bronze, Silver, Gold?”
The real question is:
- “What responsibilities need to exist in this architecture?”
When You Probably DON’T Need a Silver Layer
You may be able to skip the Silver layer if:
1. Your Data Sources Are Stable
If your systems are already clean and reliable, heavy standardization may be unnecessary.
2. You Have Limited Use Cases
If only one or two reports consume the data, reusable transformation layers may not provide enough value.
3. Your Team Is Small
Small teams often benefit from simplicity over architectural purity.
4. You Need Speed Over Scalability
For rapid development or MVP projects, fewer layers can reduce delivery time.
5. Business Logic Is Simple
If transformations are lightweight and domain-specific, Gold-layer processing may be sufficient.
When You SHOULD Use a Silver Layer
A Silver layer becomes extremely valuable when:
1. Multiple Teams Use the Same Data
Shared standardized datasets reduce duplication and inconsistencies.
2. Data Comes From Many Sources
Complex ingestion environments benefit from centralized standardization.
3. Data Quality Is a Major Concern
The Silver layer is ideal for:
- Validation
- Deduplication
- Error handling
- Data cleansing
4. Governance Matters
Enterprises with compliance requirements often need clearly governed transformation stages.
5. Scalability Is a Priority
Reusable transformation logic supports long-term platform growth.
Power BI and Microsoft Fabric Considerations
In Microsoft Fabric specifically, the Medallion pattern is heavily encouraged because Fabric naturally supports:
- Lakehouses
- Data engineering pipelines
- Shared semantic models
- Centralized governance
However, that doesn’t mean every Fabric implementation requires all three layers.
A common mistake is blindly copying enterprise patterns into small or mid-sized environments.
Good architecture should be:
- Intentional
- Practical
- Business-driven
- Maintainable
Not just fashionable.
The Best Architectural Principle: Start Simple
One of Marthe’s strongest points is that architecture can evolve.
You do not need to design for maximum complexity on day one.
A smart approach is:
Start Simple
Begin with:
- Bronze → Gold
Then evolve only when necessary.
Add Silver When Reusability Emerges
Introduce standardization once:
- Multiple domains appear
- Logic duplication increases
- Governance becomes necessary
This avoids premature overengineering while still supporting scalability.
Key Takeaways
You Don’t Need a Silver Layer Just Because Everyone Else Has One
Architecture should solve real problems not follow trends.
Every Layer Must Have Clear Responsibility
If nobody owns the layer, it becomes operational overhead instead of business value.
Standardization Matters at Scale
The larger and more complex your environment becomes, the more valuable reusable transformation layers become.
Simplicity Is Often Better
Especially for:
- Small teams
- Focused analytics
- Limited reporting scenarios
Architecture Should Evolve
Your data platform should adapt to:
- Growth
- New use cases
- Governance requirements
- Business complexity
Final Thoughts
The Silver layer debate isn’t really about technology.
It’s about intentional architecture.
Some organizations absolutely need a robust standardization layer to support enterprise-scale analytics. Others create unnecessary complexity by implementing architectural patterns they don’t truly need.
The best architects don’t blindly follow templates.
They design systems around:
- Ownership
- Reusability
- Governance
- Simplicity
- Scalability
And sometimes, the smartest architecture is the simplest one.
Learn More About Power BI & Fabric
If you want to deepen your knowledge of Power BI, Microsoft Fabric, data modeling, and architecture best practices, check out this excellent training resource:
