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Using a medallion architecture for lakehouse data

The medallion architecture offers a structured and efficient way to manage data within a lakehouse. By categorizing data into bronze, silver, and gold layers, businesses can streamline their data processes, ensure clarity, and optimize performance. This incremental enhancement, coupled with governance, paves the way for advanced analytics and machine learning endeavors

Understanding the medallion architecture

The medallion architecture categorizes data into three distinct layers:

  • Bronze layer:

    • Here, raw data flows in from various sources—databases, APIs, files, and more.
    • Data pipelines ingest, validate, and load the information.
    • Metadata, such as load timestamps and process IDs, is captured.
  • Silver layer:

    • In the silver layer, minimal transformations occur.
    • Data is cleansed and conformed, ensuring agility and speed.
    • The focus is on ELT (extract, load, transform) to quickly move data into the lakehouse.
  • Gold layer:

    • The gold layer represents the final, consumption-ready state.
    • Complex business rules, aggregations, and cross-referencing take place here.
    • Data scientists and analysts leverage this layer for advanced analytics and machine learning.

Business value of the medallion architecture

  • Data quality assurance:

    • The structured process ensures data quality progression from raw to curated layers.
    • High-quality data fuels confident decision-making.
  • Incremental data enrichment:

    • As data advances through layers, it becomes more valuable.
    • Incremental enrichment allows for efficient updates without reprocessing entire datasets.
  • Unified platform

    • The lakehouse, combining data lake and data warehouse capabilities, provides a unified platform.
    • It bridges the gap between data engineering and analytics, streamlining workflows.

Data pipelines: the backbone of the medallion architecture

  • Data ingestion (bronze layer):
    • Pipelines extract raw data from external sources.
    • Change data capture techniques ensure efficient data capture.
  • Data transformation (silver layer):
    • Minimal transformations cleanse and conform data.
    • Agility and speed are prioritized.
  • Data enrichment (gold layer):
    • Complex business rules and aggregations enhance data.
    • Advanced analytics and machine learning thrive here.

In summary, the medallion architecture, supported by robust data pipelines, ensures data quality, governance, and performance within the lakehouse. It empowers organizations to unlock the full potential of their data assets, driving innovation and informed decision-making .

For more information

Here are some good sources to learn more about the medallion architecture