In this lesson, you will learn how to structure your analytical data platform using the Medallion Architecture to create a reliable, scalable pipeline from raw ingestion to business-ready reporting.
The Medallion Architecture organizes data into three logical layers, progressively increasing the data’s quality and structure as it moves through your pipeline:
1. The Bronze Layer (Raw)
This is your "landing zone." Data is ingested from source systems in its original format. You perform minimal transformations here—typically just adding audit metadata like ingestion_timestamp or source_system_id. It acts as an immutable history of your data, allowing you to reprocess information if upstream schemas change.
2. The Silver Layer (Cleansed)
In the Silver layer, data undergoes standardization. This is where you apply the cleaning techniques we covered previously: removing duplicate records, validating data types, and filtering out noise. By the time data reaches Silver, it should be filtered and augmented, providing a "single source of truth" for engineering and data science teams.
-- Example: Moving from Bronze to Silver
INSERT INTO silver_sales
SELECT
CAST(order_id AS INT),
TRIM(customer_name) AS customer_name,
COALESCE(amount, 0) AS amount
FROM bronze_sales
WHERE order_id IS NOT NULL; -- Filter out invalid records
3. The Gold Layer (Business-Ready)
The Gold layer is designed for performance and consumption. Data here is modeled into aggregates, dimensional models, or highly specific datasets tailored for business KPIs. You are likely calculating metrics, such as period-over-period performance or median values, ensuring the final output is optimized for BI dashboards or executive reporting.
Why this structure works
By decoupling these stages, you ensure that errors in business logic (Gold) don't require re-ingesting the raw data (Bronze). It allows for modular development, where data quality checks can be inserted between each layer to ensure that downstream analytical models are always working with high-integrity, predictable schemas. This architectural discipline is the foundation of modern data engineering, turning chaotic raw inputs into trusted business intelligence.
Key Takeaway: The Medallion Architecture uses a staged approach—Bronze for raw history, Silver for cleansed standardization, and Gold for business-ready aggregation—to ensure data integrity throughout the analytical lifecycle.