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Modern data teams don’t fail because of lack of tools.
They fail because of poor data structure.
If your reports break unexpectedly, metrics don’t match across dashboards, or your Power BI model feels fragile—you don’t have a tooling problem.
You have an architecture problem.
The Medallion Architecture solves this.
The Core Idea
At its simplest, the Medallion Architecture is about layering your data so that each stage has a clear responsibility.
Instead of messy, tangled pipelines, you get a structured flow:
Each layer builds on the previous one.
No shortcuts. No mixing responsibilities.
Now if you want to skip reading and watch a 5 minutes YouTube video explaining this concept, then watch it here:
For others, lets continue reading :) :)
🥉 Bronze Layer — Raw, Untouched Data
This is your foundation layer.
Think of Bronze as a data lake landing zone where everything arrives exactly as it is.
What goes into Bronze:
Raw extracts from databases
CSV uploads
API responses (JSON)
Logs and event streams
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Key Rules:
No transformations
Append-only (never delete/update)
Full history preserved
Include metadata (timestamp, source)
Why this matters
Bronze is your insurance policy.
If business logic changes tomorrow, you don’t panic.
You simply rebuild downstream layers.
Without Bronze, you’re stuck fixing broken reports instead of fixing the root cause.
🥈 Silver Layer — Where Data Becomes Reliable
This is the most important layer.
And the one most teams either skip—or get wrong.
Silver is where data is:
Cleaned
Validated
Standardized
Joined
Typical transformations:
Bronze.Customers
↓
[Remove nulls]
[Deduplicate]
[Standardize formats]
[Apply business rules]
↓
Silver.Customers
What happens here:
Duplicate records removed
Data types fixed (dates, currency)
Business rules applied
Tables joined into meaningful structures
Data quality checks enforced
Key Principles:
Deterministic → Same input = same output
Reusable → Used by multiple reports
Documented → Every transformation is explainable
Centralized → Fix once, benefit everywhere
The Big Shift
Most beginners clean data in:
Power Query
DAX
Excel
That’s a mistake.
All data cleaning belongs in Silver.
Because:
If you fix data in reports, you fix it 10 times.
If you fix it in Silver, you fix it once.
🥇 Gold Layer — Built for Speed & Business
Gold is where data becomes decision-ready.
This is your:
Power BI semantic model
Star schema
Aggregated tables
Structure:
┌──────────────┐
│ Dim_Date │
├──────────────┤
│ Dim_Product │
├──────────────┤
│ Dim_Customer │
└──────┬───────┘
↓
┌──────────────┐
│ Fact_Sales │
└──────────────┘
What happens here:
Metrics are pre-calculated
Data is aggregated
Business terms replace technical fields
Performance is optimized
Examples:
Total Revenue
Profit Margin
Customer Segmentation
Monthly Sales Summary
Why Gold exists
Because computing everything on-the-fly is slow.
Gold ensures:
Fast dashboards
Consistent metrics
Self-service analytics
How It All Connects (End-to-End Flow)
Let’s say you have 3 data sources:
POS system
Online store
Marketplace API
Your pipeline looks like this:
Why This Architecture Works
1. Separation of Concerns
Each layer does one job—and does it well.
2. Reusability
Silver becomes the single source of truth for all reports.
3. Scalability
You can add new data sources without breaking existing models.
4. Auditability
You can trace any number in a dashboard back to its origin.
5. Performance
Gold ensures reports are fast—even with large datasets.
Common Mistakes (Avoid These)
❌ Skipping Silver
Going directly from raw data to Power BI.
→ Leads to messy DAX, inconsistent metrics, and chaos.
❌ Transforming in Bronze
Trying to “optimize early.”
→ You lose the ability to rebuild logic later.
❌ Overloading Gold
Creating too many aggregated tables.
→ Storage explodes, refresh slows down.
❌ No Data Lineage
Not knowing where a number comes from.
→ Zero trust in data.
❌ Fixing Data in Reports
Using Power Query/DAX for cleaning.
→ Every report becomes its own pipeline.
Where This Fits
The Medallion Architecture is ideal if you:
Work with multiple data sources
Build Power BI dashboards
Use Microsoft Fabric / Databricks / Snowflake
Handle growing datasets
It may be overkill if:
You have a single small dataset
No transformation complexity
No scaling requirement
Medallion vs Star Schema (Quick Clarity)
Medallion Architecture → Organizes your pipeline
Star Schema → Organizes your reporting layer
They are not competitors.
They work together.
What You Should Do Next
If you’re currently building dashboards:
Map your current pipeline
Identify missing layers
Start with Bronze (easy win)
Invest heavily in Silver
Keep Gold focused and lean
Final Thought
Most data problems are not technical.
They’re structural.
The Medallion Architecture gives you:
Clarity
Control
Confidence
And once you implement it properly,
you’ll never go back to messy pipelines again.
Let’s Talk
What does your current setup look like?
Direct from raw data?
Partial layering?
Fully structured pipeline?
Reply and let me know—I read every response.
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Atikant Jain
Your Analytical Guy
admin@analyticalguy.tech
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