Medallion Architecture
The Medallion Architecture is a structured approach to organising data in a lakehouse by layering it into distinct tiers: Bronze, Silver, and Gold. This framework improves data quality, governance, and performance for analytical and machine learning workloads.
Key Layers in the Medallion Architecture
1. Bronze Layer (Raw Data)
- Stores raw, ingested data from various sources (databases, logs, APIs, IoT devices).
- Maintains fidelity, including duplicates, missing values, and unstructured formats.
- Used for historical tracking, compliance, and replayability.
2. Silver Layer (Cleansed & Enriched Data)
- Applies transformations like deduplication, schema enforcement, and error correction.
- Standardises formats for easier querying and integration.
- Acts as a reliable single source of truth for operational analytics.
3. Gold Layer (Business-Ready Data)
- Contains aggregated, curated datasets optimised for reporting and machine learning.
- Tailored for end-user consumption in dashboards, AI models, and decision-making.
- Often structured in a star schema or denormalised format for performance.
Why Use the Medallion Architecture?
- Improved Data Governance – Ensures clean, well-managed data with lineage tracking.
- Scalability & Flexibility – Supports structured, semi-structured, and unstructured data at scale.
- Performance Optimisation – Reduces computational overhead by staging transformations.
- Enhances Analytics & AI – Delivers high-quality data for BI, AI/ML, and real-time use cases.
Technology Alignment
The architecture is commonly implemented in lakehouse platforms like Databricks, Apache Iceberg, and Delta Lake, enabling ACID transactions, schema evolution, and time travel.
By structuring data in progressive layers, organisations can enhance reliability, reduce processing costs, and unlock faster, more informed decision-making.