Medallion Architecture

Medallion Architecture is a data lake architecture design pattern that organizes data into different layers to improve data quality, reliability, and performance. This approach is particularly beneficial in Azure Data Engineering, leveraging services like Azure Data Lake Storage, Azure Databricks, and Azure Synapse Analytics.

Overview of Medallion Architecture

Medallion Architecture typically consists of three main layers:


Bronze Layer(Raw Data)
Silver Layer(Cleaned and Enriched Data)
Gold Layer(Aggregated and Curated Data)


Medallion Architecture Diagram


Bronze Layer: Raw Data

  • Purpose:Ingest raw data from various sources without transformation.
  • Storage:Azure Data Lake Storage (ADLS) Gen2 or Azure Blob Storage.
  • Characteristics
    • Contains raw, unprocessed data.
    • Stores data in its original format (e.g., JSON, CSV, Parquet).
    • Acts as a data archive for historical analysis.

Silver Layer: Cleaned and Enriched Data

  • Purpose:Clean, filter, and transform data for quality and consistency.
  • Storage:ADLS Gen2, Azure SQL Database, or Azure Synapse Analytics.
  • Characteristics
    • Data is cleaned and transformed (e.g., missing values handled, duplicates removed).
    • Enrichment with additional metadata or lookup tables.
    • Intermediate step for creating reliable datasets.

Gold Layer: Aggregated and Curated Data

  • Purpose:Provide high-quality, aggregated data for analytics and reporting.
  • Storage:ADLS Gen2, Azure SQL Database, Azure Synapse Analytics, or Power BI.
  • Characteristics
    • Highly curated and aggregated data.
    • Optimized for business intelligence and reporting.
    • Supports dashboards, machine learning models, and advanced analytics.

Benefits of Medallion Architecture

Scalability: Handles large volumes of data efficiently.
Data Quality: Improves data quality through structured transformation layers.
Performance: Optimizes data for different use cases (e.g., raw data storage, analytical queries).
Flexibility: Supports a wide range of data sources and formats.
Governance: Enhances data governance and traceability across different layers.