Designing a Clean Medallion Architecture in Databricks for Real Reporting Needs
Most reporting problems do not come from Power BI or visualization tools.
They come from how the data is organized before it reaches the reporting layer.
A lot of teams try to push raw CRM tables, ERP extracts, finance dumps, and timesheet files directly into Power BI models. This usually leads to slow refreshes, constant model changes, broken relationships, and inconsistent metrics across teams.
A clean Medallion Architecture solves these issues by giving your data a predictable, layered structure inside Databricks. It gives reporting teams clarity, improves performance, and reduces rework across projects.
Below is a senior-level view of how to design and implement it in a way that supports long-term reporting needs.
Why the Medallion Architecture Matters
The Medallion model gets discussed often, but in practice the value comes from discipline and consistency. The real benefit is not the three layers. It is the separation of responsibilities:
- a. Bronze captures data in the state it arrives
- b Silver corrects and standardizes data
- c. Gold reshapes the data for analytics
This separation ensures data engineers, analysts, and reporting teams do not step on each other’s work.
You avoid the common trap of mixing raw, cleaned, and aggregated data in the same folder or the same table, which eventually turns the lake into a “large folder with files,” not a structured ecosystem.
Bronze Layer: The Record of What Actually Arrived
The Bronze layer should be the most predictable part of your data platform.
It contains raw data as received from CRM, ERP, HR, finance, or external systems.
From a senior perspective, the bronze layer has two primary responsibilities:
- Capture everything exactly as it arrived
- Store enough metadata to regenerate or audit any pipeline
This means storing load timestamps, file names, and source identifiers.
The Bronze layer is not the place for business logic.
Any adjustment here will compromise traceability.
A good bronze table lets you answer questions like:
“What exactly did we receive from Business Central on the 7th of this month?”
If your Bronze layer cannot answer this, it needs improvement.
Silver Layer: Apply Business Logic Once, Use It Everywhere
Silver Layer: Apply Business Logic Once, Use It Everywhere
The Silver layer transforms raw data into standardized, trusted datasets.
A senior approach focuses on solving root issues here, not patching them later.
Typical responsibilities include:
- a. Standardizing column names across systems
- b. Aligning data types
- c. Removing duplicates
- d. Handling slowly changing dimensions
- e. Resolving inconsistent reference data
- f. Combining similar entities (for example, multiple CRM lead sources)
This is where you remove all the “noise” that Power BI models should never see.
Silver is also where cross-functional logic goes.
For example:
- a. Standardizing time dimensions
- b. Normalizing currencies
- c. Validating project, customer, or employee master records
Once the Silver layer is stable, the Gold layer becomes significantly simpler.
Gold Layer: Data Structured for Reporting and Performance
Gold is the presentation layer of the Lakehouse.
It contains datasets that match your reporting use cases, not the way source systems store data.
A senior-level Gold layer focuses on:
- a. Fact and dimension tables
- b. Aggregated views
- c. Flattened models for Power BI
- d. Denormalized tables where it improves performance
- e. Stable schemas that do not break dashboards
Gold tables should reflect business definitions, not technical ones.
If your teams rely on metrics like utilization, revenue recognition, resource cost rates, or customer lifetime value, those calculations should live here.
Gold is also where performance tuning matters.
Partitioning, Z-ordering, and optimizing Delta tables significantly improves refresh times and Power BI performance.
A Real-World Example
In projects where CRM, Finance, HR, and Project data come from different systems, reporting becomes difficult when each department pulls data separately.
A Medallion architecture simplifies this:
- Bronze stores raw CRM leads, raw financial transactions, and raw timesheets exactly as received.
- Silver standardizes customer IDs, aligns employee records, and fixes missing reference data.
- Gold produces reporting-ready tables such as:
- Customer 360
- Project financial summary
- Timesheet utilization
- Revenue snapshots
- Management dashboard datasets
The reporting team consumes these gold tables directly in Power BI with minimal transformations.
Why This Architecture Works for Reporting Teams
- Consistent Data
Different Power BI reports use the same Gold tables, so numbers match across dashboards. - Stable Schema
Silver and Gold layers change only through controlled updates, reducing broken reports. - Faster Refresh
Clean, optimized gold tables refresh faster than raw or semi-transformed data. - Easier Collaboration
Data engineers work on pipelines, and reporting teams focus on visuals and DAX. - Unified View of the Business
Departments no longer have their own conflicting datasets.
To conclude, a clean Medallion Architecture is not about technology – it’s about structure, discipline, and clarity. When implemented well, it removes daily friction between engineering and reporting teams.
It also creates a strong foundation for governance, performance, and future scalability.
Databricks makes the Medallion approach easier to maintain, especially when paired with Delta Lake and Unity Catalog. Together, these pieces create a data platform that can support both operational reporting and executive analytics at scale.
We hope you found this blog useful, and if you would like to discuss anything, you can reach out to us at transform@cloudFronts.com
