• Pradip
• 17 Dec, 2025
• 0 Comments
• 3 Mins Read

Medallion Architecture in Azure Data Engineering Explained

Introduction

Modern data platforms must handle massive data volumes, multiple data sources, and complex analytics requirements all while ensuring data quality, scalability, and performance. In Azure Data Engineering, one architectural pattern has emerged as a best practice for building reliable and scalable data pipelines: Medallion Architecture.

Popularized by Databricks and widely adopted across Azure data platforms, Medallion Architecture organizes data into incremental layers that progressively improve data quality and structure. This blog explains Medallion Architecture in detail, its layers, Azure services involved, benefits, and real-world use cases.

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What is Medallion Architecture?

The Medallion Architecture is a data design pattern that logically organizes data into three distinct layers: Bronze, Silver, and Gold. The goal is to incrementally improve the quality, structure, and reliability of data as it flows through each stage.

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Why Use Medallion Architecture in Azure?

Azure environments deal with:

• Streaming and batch data

• Multiple data formats

• High-scale analytics

• Data governance requirements

Medallion Architecture helps by:

• Separating raw and processed data

• Supporting incremental transformations

• Improving data reliability and performance

• Simplifying debugging and reprocessing

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Medallion Architecture Layers Explained

1. Bronze Layer – Raw Data

Purpose

The Bronze layer stores raw, unprocessed data exactly as it arrives from source systems.

Characteristics

• No transformations

• Append-only data

• Schema may evolve

• Acts as a historical record

Typical Data Sources

• Azure Data Factory pipelines

• Event Hub / IoT Hub streams

• REST APIs

• On-prem databases

• SaaS applications (CRM, ERP)

Azure Services Used

• Azure Data Lake Storage Gen2

• Azure Data Factory

• Azure Databricks

• Azure Event Hubs

Example

Raw sales transactions ingested from multiple regions in JSON/CSV format.

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2. Silver Layer – Cleaned & Enriched Data

Purpose

The Silver layer improves data quality and applies business rules.

Transformations Performed

• Data cleansing (remove nulls, duplicates)

• Schema enforcement

• Data type casting

• Joins between datasets

• Standardization

Characteristics

• Structured and validated

• Consistent schema

• Suitable for analytics and reporting

Azure Services Used

• Azure Databricks (Spark)

• Delta Lake

• Azure Synapse Spark Pools

Example

Sales data joined with customer master data, cleaned, and standardized.

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3. Gold Layer – Business-Ready Data

Purpose

The Gold layer contains aggregated and optimized data for business users.

Transformations Performed

• Aggregations (daily, monthly KPIs)

• Business logic

• Calculated metrics

• Data modeling (star/snowflake schemas)

Characteristics

• Highly structured

• Optimized for performance

• Used for dashboards and reporting

Azure Services Used

• Azure Synapse Analytics (Dedicated SQL Pool)

• Azure Databricks SQL

• Power BI

• Azure Analysis Services

Example

Monthly revenue by region and product category.

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Data Flow in Medallion Architecture

Each layer builds upon the previous one, ensuring data traceability and reusability.

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Role of Delta Lake in Medallion Architecture

Delta Lake plays a critical role by providing:

• ACID transactions

• Schema enforcement & evolution

• Time travel

• Efficient updates and deletes

These features make Medallion Architecture reliable and production-ready in Azure.

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Benefits of Medallion Architecture

1. Improved Data Quality

Each layer applies validations and rules, reducing errors downstream.

2. Scalability

Works efficiently with large-scale batch and streaming workloads.

3. Easier Debugging

Issues can be traced back to the exact layer where they occurred.

4. Reusability

Silver data can serve multiple business use cases.

5. Governance & Compliance

Raw data is preserved for audits and reprocessing.

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Medallion Architecture vs Traditional Data Warehousing

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Real-World Use Case

Healthcare Analytics Platform

• Bronze: Raw patient records from multiple hospitals

• Silver: Cleaned patient data with standardized codes

• Gold: Aggregated reports for diagnosis trends and compliance dashboards

This approach ensures accuracy, compliance, and fast reporting.

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Best Practices for Azure Medallion Architecture

• Use Delta Lake for all layers

• Apply schema validation in Silver

• Keep Bronze immutable

• Automate pipelines using ADF

• Monitor performance with Azure Monitor

• Secure data using RBAC and encryption

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Conclusion

Medallion Architecture is a powerful and flexible design pattern for Azure Data Engineering. By separating data into Bronze, Silver, and Gold layers, organizations can build scalable, reliable, and high-quality data platforms.

Whether you’re building analytics dashboards, machine learning pipelines, or enterprise data lakes, Medallion Architecture ensures your data is trusted, traceable, and business-ready.

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