The Medallion architecture is a data design pattern used in data platforms that organizes data into progressive quality layers, typically Bronze → Silver → Gold. Each layer represents increasing levels of cleansing, structure, and business value. Peliqan fully supports building up a Medallion architecture, as described in this article.

The layers

Bronze

Raw data from data sources:

Tables created by the Peliqan ELT pipelines
Raw tables from connected databases

Silver

Cleaned & structured data:

Schema enforcement (e.g. column selection)
Data normalization (e.g. unified VAT numbers for customer records from a CRM)
Deduplication
Basic joins and transformations

This layer becomes the reliable analytical data.

Gold

Business ready data:

Aggregated tables
KPIs and metrics
Dimensional models (e.g. star schema)
Data optimized for BI tools like Power BI and Metabase

This layer serves dashboards, ML features, reporting, AI Chatbots and AI Agents

How to implement a Medallion architecture in Peliqan

Data transformations are implemented in Peliqan using a combination of SQL queries and low-code Python scripts. Both can be implemented with the support of Peliqan’s AI Data Engineer. The bronze layer consists the raw tables from e.g. ELT pipelines (SaaS connections). The silver layer and golden layer is implemented using SQL queries, and optionally Python scripts (Data apps). SQL queries are typically grouped in a schema called “Silver” and “Gold”. Example using schema’s, the ELT target schemas are the bronze layer:

Bronze, Silver and Gold layers organized as schemas

However, you can also use Peliqan’s labels to group queries into Bronze, Silver and Gold layers, e.g. when you want to use multiple schemas within one layer. Example using labels:

Queries grouped into Bronze, Silver and Gold layers with labels

Transformations are implemented in a query, which can optionally be materialized (table replication). More info: Materialize & Replicate Queries in the next layer consume layers in the layer below. See examples below. Peliqan’s data lineage helps to keep track of the dependency between queries:

Data lineage showing dependencies between queries across layers

Simplified example of queries in Silver and Gold layer

Examples tables in the Bronze layer (from ELT pipelines):

exact_online.customers
exact_online.sales_invoices

Example queries in the Silver layer with column selection, normalizing VAT numbers etc:

-- query "customers" in Silver layer
SELECT 
    id                    AS customer_id,
    name                  AS customer_name,
    city                  AS customer_city,
    REPLACE(vat, '.', '') AS customer_vat
FROM exact_online.customers     # ELT pipeline target table (bronze layer)

-- query "invoices" in Silver layer
SELECT
   id                     AS invoice_id,
   amount                 AS invoice_amount,
   customer_id            AS invoice_customer_id
FROM exact_online.sales_invoices

-- query "customer_revenue" in Silver layer
SELECT * FROM silver.customers c
LEFT JOIN silver.invoices i ON
c.id = i.invoice_customer_id

Example query in the Gold layer:

-- query "customer_revenue" in Gold layer
SELECT
   SUM(invoice_amount),
   customer_id
FROM silver.customer_revenue
GROUP BY customer_id

The queries in the Gold layer are typically configured as “Views” to make them visible for external consumers, e.g. a BI tool.

Basics

Advanced

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Medallion architecture

The layers

Bronze

Silver

Gold

How to implement a Medallion architecture in Peliqan

Simplified example of queries in Silver and Gold layer

​The layers

​Bronze

​Silver

​Gold

​How to implement a Medallion architecture in Peliqan

​Simplified example of queries in Silver and Gold layer

The layers

Bronze

Silver

Gold

How to implement a Medallion architecture in Peliqan

Simplified example of queries in Silver and Gold layer