Medallion Architecture: Build a Bronze, Silver and Gold Data Pipeline

The diagram shows how data moves across the three layers. Each stage improves the quality of data and prepares it for the next step.

• Bronze: Raw customer, order and payment data enters the system.
• Silver: The data is cleaned, checked and organised.
• Gold: The processed data is used to create sales reports, customer insights and business dashboards.

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What Are the Three Layers of Medallion Architecture?

Medallion Architecture divides data into three layers: Bronze, Silver and Gold. Each layer has a different purpose. Data starts in its original form, gets cleaned and checked, and is finally prepared for business use.

Bronze Layer: Raw Data

The Bronze layer is the first stage of Medallion Architecture. It stores raw data collected from different sources without making major changes to it.

For example, an online shopping company may collect data from its website, customer database and payment system. This data may include customer details, order records, payment information and product searches.

The Bronze layer stores this information in its original form.

What happens in the Bronze layer?

• Collects data from different sources, such as websites, databases and applications.
• Stores data in its original format.
• Keeps a record of incoming data for future use.
• Makes it possible to process the raw data again if needed.

Example: An online shopping company receives 500 customer orders in a day. The Bronze layer stores these order records as they arrive, even if some entries contain missing details or duplicate records.

Silver Layer: Cleaned and Validated Data

Once data enters the Bronze layer, it moves to the Silver layer for cleaning and validation. The main purpose of this layer is to improve data quality and make information more reliable.

For example, an online shopping company may have duplicate customer records or incomplete order details. The Silver layer helps identify and fix these issues before the data is used for analysis.

What happens in the Silver layer?

• Removes duplicate records.
• Identifies and handles missing or incorrect information.
• Standardises data formats, such as dates and phone numbers.
• Checks whether the data follows the required rules.
• Organises information so it can be used for further analysis.

Example: The company may find that the same customer appears twice in its records. The Silver layer helps identify the duplicate entries and organise the customer information into a consistent format.

Gold Layer: Business-Ready Data

The Gold layer is the final stage of Medallion Architecture. It takes cleaned data from the Silver layer and prepares it for business use.

At this stage, data is organised to answer specific business questions. Companies can use it to study sales, understand customer behaviour and track product performance.

What happens in the Gold layer?

• Combines related information from different datasets.
• Calculates useful figures, such as total sales and average order value.
• Organises data for business reports and dashboards.
• Creates datasets for business analysis and decision-making.

Example: The online shopping company can combine customer and order data to find its total monthly sales, most popular products and repeat customers. Teams can use this information to plan offers, manage stock and improve their marketing campaigns.

Before Proceeding further, also understand Data architecture with examples

Bronze vs Silver vs Gold: Key Differences

All three layers work together, but they handle data at different stages.

Understand: What Is Data?

How to Build a Data Pipeline Using Medallion Architecture

Now that we understand the three layers, let's see how they work together in a real data pipeline. Consider an online shopping company that wants to track customer orders, sales and product performance. It can use Medallion Architecture to collect, clean and organise this information in three steps.

Step 1: Collect Raw Data in the Bronze Layer

The first step is to collect data from different sources and store it in the Bronze layer.

For an online shopping company, these sources can include:

• Website activity, like product searches, clicks and orders.
• Customer databases containing names, contact details and addresses.
• Payment systems containing payment and refund records.

The Bronze layer stores this information in its original form. It does not remove duplicate entries or correct missing details at this stage.

Example: Suppose the company receives 500 orders in one day. It stores all 500 order records in the Bronze layer, including entries that may have missing details or duplicate information.

Step 2: Clean and Validate Data in the Silver Layer

Once the raw data is stored, it moves to the Silver layer. Here, the company checks the records and fixes common data issues.

The process includes:

• Removing duplicate customer and order records.
• Identifying missing or incorrect information.
• Using consistent formats for dates, addresses and other details.
• Checking whether the records meet the required data quality rules.

Example: Out of the 500 order records, suppose some contain duplicate entries or incorrect customer details. The Silver layer helps identify these issues and prepares a cleaner set of records for analysis.

Step 3: Prepare Business-Ready Data in the Gold Layer

After cleaning and validation, the data moves to the Gold layer. The company now organises it to answer specific business questions.

For example, it can:

• Calculate total daily and monthly sales.
• Find the average order value.
• Identify the most popular products.
• Track repeat customers and their buying habits.
• Prepare datasets for business reports and dashboards.

Example: The company combines cleaned customer and order records to find out which products sell the most and how much customers spend on average. The sales and marketing teams can use these insights to plan offers, manage inventory and improve their campaigns.

Medallion Architecture Example: Online Shopping Data Pipeline

Here is a quick look at how the same data moves across all three layers:

The three layers work together to turn raw information into useful business data. This makes it easier for teams to analyse information, track performance and make decisions.

Also Understand: Benefits and Advantages of Big Data

Medallion Architecture vs Lakehouse Architecture

Medallion Architecture and Lakehouse Architecture are closely related, but they serve different purposes. Lakehouse Architecture provides a platform to store and manage data, while Medallion Architecture organises that data into different layers. Many organisations use both together to build and manage their data pipelines.

What Is Lakehouse Architecture?

Lakehouse Architecture is a data management approach that combines features of data lakes and data warehouses.

A data lake stores large amounts of raw data in different formats. A data warehouse stores organised data that businesses can use for reporting and analysis. A lakehouse brings these capabilities together in one platform.

It allows businesses to store different types of data and use the same platform for data processing, analytics and reporting.

What Is Databricks Medallion Architecture?

Databricks uses Medallion Architecture to organise data into three layers: Bronze, Silver and Gold. Each layer improves the quality of data and prepares it for the next stage.

The Databricks platform supports this process using tools and features such as:

• Delta Lake: Helps store and manage data in tables. It also supports reliable data updates and changes.
• Lakeflow: Helps build, run and manage data pipelines.
• Unity Catalog: Helps manage data access, permissions and governance.

These tools help organisations manage data across the three layers. However, Medallion Architecture is not limited to Databricks. It can also be used with other data platforms.

Also Read: Relational Database vs Non-Relational Databases 

Medallion Architecture vs Lakehouse Architecture: Key Differences

Although these two approaches often work together, their roles are different.

In simple terms, Lakehouse Architecture provides the platform, while Medallion Architecture provides a way to organise the data stored on it. Together, they help businesses manage data and prepare it for analysis and reporting.

Helpful Read: Difference Between Data Science and Data Analytics 

Benefits, Challenges and Best Practices of Medallion Architecture

Medallion Architecture helps businesses manage large amounts of data in an organised way. It improves data quality and makes information easier to use for reporting and analysis. However, setting up and managing these layers also comes with a few challenges.

Benefits of Medallion Architecture

Here are some key benefits of using Medallion Architecture:

• Improves data quality: Each layer cleans and organises data before it moves to the next stage. This makes the final data more reliable.
• Keeps raw data available: The Bronze layer stores the original data. Teams can use it again if they need to correct errors or process the data differently.
• Makes data easier to manage: Dividing data into three layers helps teams understand where it comes from and how it is processed.
• Supports analytics and reporting: The Gold layer provides organised data that businesses can use to create reports, dashboards and insights.
• Supports machine learning: Clean and well-organised data can be used to build and train machine learning models.

Challenges of Medallion Architecture

Although this approach offers several benefits, businesses may face some challenges while setting it up and managing it.

• Higher storage costs: Data is stored across multiple layers, which can increase storage requirements and costs.
• More processing requirements: Cleaning, validating and transforming large amounts of data requires computing resources.
• Pipeline management: Businesses need to monitor each layer to make sure data moves correctly from Bronze to Silver and Gold.
• Data quality issues: Errors in the earlier stages can affect the quality of data in the later layers.
• Security and access control: Organisations must manage who can view or change data across different layers.

Also Understand: Data Modeling for Big Data and Data Modeling for Data Integration

Best Practices for Building Medallion Architecture

Businesses can follow these practices to build and manage their data pipelines more effectively:

• Keep raw data unchanged: Store the original data in the Bronze layer so it remains available for future use.
• Set data quality rules: Check for missing values, duplicate records and incorrect information in the Silver layer.
• Build Gold datasets around business needs: Prepare data based on what teams need for reports, dashboards and analysis.
• Track data movement: Maintain data lineage to understand where data comes from and how it changes across layers.
• Monitor data pipelines: Check pipeline performance regularly and fix errors before they affect other layers.
• Manage data access: Set permissions to make sure only authorised users can access or modify data.

Conclusion

Medallion Architecture helps businesses turn raw data into useful information using three layers: Bronze, Silver and Gold. Each layer has a clear role in collecting, cleaning and preparing data for business use. When planned and managed well, this approach makes data pipelines easier to organise and supports better reporting, analytics and business decisions.

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