The Medallion Architecture is a data lakehouse architecture pattern popularized by Databricks. It’s designed to progressively refine data through a series of layers, ensuring data quality and suitability for various downstream consumption needs. The name “Medallion” refers to the distinct quality levels achieved at each layer, similar to how medals signify different levels of achievement.

The architecture typically consists of three main layers: Bronze (Raw), Silver (Curated), and Gold (Refined). Some implementations might include additional optional layers, but these three form the core of the pattern.

Here’s a breakdown of each layer:

1. Bronze Layer (Raw or Landing Zone):

• Purpose: This is the entry point for all data ingested into the data lakehouse.
• Characteristics:
  • Contains raw, unprocessed data ingested directly from source systems.
  • Data is stored in its original format (e.g., CSV, JSON, Avro, Parquet as it comes from the source).
  • The primary goal is scalability and durability of the raw data.
  • Minimal transformations are applied at this stage, primarily focusing on data landing and basic metadata tagging (e.g., source system, ingestion timestamp).
  • Data in this layer serves as the system of record or the single source of truth for all downstream processing.
  • Retention policies are often longer in this layer to preserve historical data.
• Focus: Ingest, Store, Audit.

2. Silver Layer (Curated or Cleansed):

• Purpose: This layer focuses on data quality and standardization.
• Characteristics:
  • Data from the Bronze layer undergoes cleansing, standardization, and basic transformations.
  • This includes tasks like:
    • Data type casting and validation.
    • Handling missing values.
    • Filtering out erroneous or irrelevant data.
    • Standardizing formats and naming conventions.
    • Deduplication.
  • Data in the Silver layer is structured and conformed to a consistent schema, often using formats optimized for analytical processing (like Parquet with schema enforcement).
  • This layer aims to provide a trusted and reliable dataset for further analysis and downstream consumption.
  • Data lineage and audit trails are often established and maintained in this layer.
• Focus: Cleanse, Conform, Integrate.

3. Gold Layer (Refined or Business-Level):

• Purpose: This layer provides business-ready data optimized for specific analytical use cases and consumption by end-users.
• Characteristics:
  • Data from the Silver layer is further transformed, aggregated, and joined to create business-centric views and models.
  • This might involve:
    • Creating dimensional models (star or snowflake schemas).
    • Aggregating data for reporting and dashboards.
    • Joining data from multiple Silver tables to create business entities.
    • Applying business logic and calculations.
  • Data in the Gold layer is typically organized and structured for optimal query performance for specific analytical tools and user needs.
  • Focus is on answering business questions and providing insights.
  • Data retention policies in this layer might be tailored to specific reporting or analytical requirements.
• Focus: Aggregate, Model, Serve.

Benefits of the Medallion Architecture:

• Improved Data Quality: Progressive refinement through layers helps identify and resolve data quality issues early in the process.
• Enhanced Data Governance: Clear separation of layers allows for better control and management of data at different stages.
• Increased Reliability: Standardized and cleansed data in the Silver and Gold layers leads to more reliable analytical results.
• Simplified Consumption: The Gold layer provides business users with easily understandable and queryable data models.
• Scalability and Flexibility: Built on data lakehouse principles, it leverages scalable storage and processing capabilities.
• Separation of Concerns: Different teams can focus on specific layers based on their expertise (e.g., data engineers on Bronze and Silver, data analysts on Gold).
• Reusability: Data cleansed and conformed in the Silver layer can be reused for multiple Gold layer models.

In summary, the Medallion Architecture provides a structured and robust approach to building a data lakehouse. By progressively refining data through the Bronze, Silver, and Gold layers, organizations can ensure data quality, improve governance, and ultimately derive more valuable insights for their business.