🏅 Medallion Architecture – A Simple Guide for Beginners

What is it? The Medallion Architecture is a way to organize data in layers inside a data lake or lakehouse system. It helps turn raw data into clean, useful information step by step. The layers are usually called:

• 🥉 Bronze — Raw data
• 🥈 Silver — Cleaned and structured data
• 🥇 Gold — Final data ready for business use

It’s often used with tools like Databricks, Delta Lake, Apache Spark, and dbt, but it can work with other tools too.

🔷 Why Use Medallion Architecture?

This layered setup makes it easier to:

• Keep raw data separate from processed data
• Fix or check issues at each step
• Build scalable and reliable data pipelines
• Improve data security, quality, and team collaboration

🥉 Bronze Layer — Raw Data

Goal: Just capture the data exactly how it comes in.

What it contains:

• No changes or cleaning
• Stored in the original format
• Acts like a “backup” of what was received

Sources:

• Kafka, Kinesis (real-time streams)
• Databases (like MySQL, PostgreSQL)
• APIs, logs, sensors

Example: You collect online sales data from different stores and save it as-is.

🥈 Silver Layer — Clean and Organized Data

Goal: Make the data useful and consistent.

What happens here:

• Remove duplicates
• Fix data types (like dates and numbers)
• Clean missing or bad values
• Flatten complex data like JSON

Example: You take the raw sales data and join it with product details, fix time zones, and remove duplicates.

🥇 Gold Layer — Business-Ready Data

Goal: Provide final data that’s ready for reports, dashboards, and decision-making.

What it includes:

• Business-level summaries and metrics
• Data models like “total sales by region” or “top customers”
• Data that runs fast and is easy to use for analysis

Used by:

• BI Tools (Power BI, Tableau)
• Business teams and analysts
• Machine learning models

Example: You create a report showing weekly sales trends across all regions.

🔁 How the Data Flows

Here’s the basic pipeline flow:

Raw Data ➜ Bronze ➜ Silver ➜ Gold ➜ Dashboards & Reports        

🛒 Real Example: Retail Company

• Bronze: Save sales transactions from stores in raw format (JSON, Parquet)
• Silver: Clean the sales data, fix formats, and link it with product and store data
• Gold: Create daily and weekly sales summaries for dashboards and reports

🎯 Benefits of Using Medallion Architecture

• Modular Design: Easy to maintain and update parts without breaking the whole system
• Data Quality: Each step checks and improves data quality
• Audit Trail: Raw data is always available for reference
• Scalable: Works well for large data volumes
• Secure: Access can be controlled at each layer

🛠 Example Tech Stack

LayerTools & Technologies UsedBronzeS3, GCS, Delta Lake, Kafka, JSON, ParquetSilverSpark, dbt, Airflow, Delta, Great ExpectationsGoldDatabricks SQL, Snowflake, BigQuery, Power BI, Tableau

🧪 Extra Features You Can Add

• Data quality checks (with Great Expectations)
• Version control and data lineage
• Row-level security and access control
• Schema evolution
• Data catalog integration (like Unity Catalog or Amundsen)

⚠️ When You Might Not Need This

• If you’re only working on simple or one-time data pipelines
• If you need real-time responses with very low delay
• If your data environment is very small

📌 Summary

The Medallion Architecture organizes data into three layers — Bronze (raw data), Silver (cleaned and structured data), and Gold (business-ready data). It helps build scalable, maintainable, and secure data pipelines. Each layer adds more quality and structure, making the data ready for reporting, analysis, and decision-making. It’s widely used in modern data platforms like Databricks and Delta Lake.