Connect Bold BI to a Gold Layer Using Medallion Architecture

TL;DR: Connect Bold BI® to a Gold layer using Medallion Architecture to deliver faster dashboards, consistent KPI definitions, and scalable embedded analytics experiences. By consuming certified Gold-layer datasets, organizations can eliminate duplicated business logic, improve trust in metrics, and create a reliable foundation for data-driven decision-making.

Introduction

Imagine a growing organization where finance, sales, and operations teams all rely on data to make decisions. As analytics adoption expands, teams often build dashboards from different datasets and apply business logic independently.

The challenge is that the same KPI can be defined in multiple ways. For example, the finance team can report 8% revenue growth, while the sales team reports 11% for the same period. Although both teams are working with valid data, differences in calculations and business rules can lead to inconsistent metrics, duplicated calculations, slower dashboard performance, and reduced confidence in analytics.

This is exactly the problem Medallion Architecture is designed to solve. By refining data through Bronze, Silver, and Gold layers, organizations create a trusted foundation for analytics. Many organizations choose to connect Bold BI to a Gold layer because it centralizes business logic, standardizes KPI definitions, and delivers trusted datasets that can be used consistently across dashboards, and embedded analytics applications.

In this blog, you'll learn why organizations connect Bold BI to a Gold layer, how Gold-layer data is prepared for analytics consumption, and how Bold BI works with trusted datasets stored in Databricks, Snowflake, Microsoft Fabric, Azure Synapse, SQL Server, PostgreSQL, and other modern analytics platforms.

What Is the Medallion Architecture Gold Layer?

The Medallion Architecture Gold layer is the final, business-ready layer where data is curated for dashboards and analytics consumption. Gold-layer datasets typically include certified analytical views, data marts, fact and dimension tables, and, in some platforms, semantic models. The goal is to publish trusted, consistent KPI definitions so BI tools can visualize and analyze the same metrics across every dashboard and embedded analytics experience.

How Data Moves Through Medallion Architecture

The Medallion Architecture organizes data into multiple layers, with each layer serving a specific role in preparing data for analytics. The following diagram illustrates how data progresses from raw source systems to analytics-ready datasets through this refinement process.  

As data moves through each layer, it becomes progressively cleaner, more structured, and better suited for reliable analytics and decision-making.

Next, let's look at what happens as raw Bronze-layer data is transformed into trusted Silver and Gold-layer datasets.

Turning Bronze Data into Silver and Gold: What Happens and Where

Before data becomes analytics-ready, it passes through a series of preparation stages within the underlying data platform. These activities transform raw records into trusted Silver-layer datasets and ultimately into business-ready Gold-layer datasets. The following table summarizes the steps required to transform raw data into analytics-ready Gold-layer datasets.

Step	What Happens	Where
Raw data extraction	Read data from the Bronze layer while preserving the original records.	Bronze Layer
Data cleansing	Remove invalid values, handle missing data, and correct data quality issues.	Silver Layer
Data standardization	Apply consistent formats for dates, currencies, units, and naming conventions.	Silver Layer
Data validation	Verify required fields, data types, and acceptable value ranges.	Silver Layer
Remove duplicate records	Eliminate duplicate customer, order, and transaction records.	Silver Layer
Apply business rules	Enforce organizational rules and derive operational fields where needed.	Silver Layer
Publish Silver datasets	Store trusted datasets that become the foundation for Gold-layer modeling.	Silver Layer
Create Gold-layer models	Organize trusted Silver-layer data into business-ready analytical models.	Gold Layer
Standardize KPI definitions	Define and standardize business metrics for consistent analytics.	Gold Layer
Publish Gold-layer datasets	Deliver curated datasets ready for dashboards and analytics consumption.	Gold Layer

Most Bronze-to-Silver and Silver-to-Gold processing occurs within platforms such as Databricks, Microsoft Fabric, Snowflake, and Azure Synapse. Once the data reaches the Gold layer, analytics platforms can consume those certified datasets to deliver dashboards, analytics, and business insights. Now that we've seen how data moves through the Medallion Architecture, let's explore why the Gold layer is the preferred foundation for BI and analytics.

Why the Gold Layer Is the Best for BI and Analytics

The Gold layer is designed for business-ready analytics. It applies business logic, standardizes KPIs, and organizes trusted data into structures that can be used directly for analytics, dashboards, and decision-making.

Area	Bronze Layer	Silver Layer	Gold Layer
Primary Focus	Raw data ingestion and storage	Data cleansing, validation, and standardization	Business-ready analytics and KPI consumption
Business Logic	Not yet applied	Partially prepared	Fully standardized and aligned with business rules
KPI Standardization	KPI definitions are not established	KPI calculations may still vary across teams	Centralized and standardized KPI definitions ensure consistent analytics across the organization
Data Quality & Consistency	May contain errors, duplicates, and inconsistencies	Cleansed and validated data	Trusted, high-quality data curated for business use
Analytics Readiness	Not intended for direct analytics consumption	Requires additional preparation and modeling	Ready for dashboards, self-service analytics, and business analysis
Governance & Scalability	Limited business context and governance	Improved governance through standardized data	Centralized business logic supports governed and scalable analytics
Primary Users	Data engineers and operations teams	Data teams and analysts	Business users, analysts, and decision-makers

The Gold layer provides the business context and consistency that BI platforms need to deliver reliable analytics. With trusted data, standardized KPIs, and centralized business logic, it provides a strong foundation for dashboards, self-service analytics, and decision-making.

Now, let's look at how BI platforms access and use Gold-layer data to deliver analytics experiences.

How BI Platforms Access Gold-Layer Data

Once Gold-layer datasets are available, organizations can connect Bold BI to a Gold layer to build dashboards, self-service analytics experiences, and embedded analytics applications using trusted business data.

Most modern BI platforms support connections to databases, data warehouses, lakehouses, and cloud analytics platforms where Gold-layer data is stored.

The key principle is to keep core business logic and KPI definitions in the Gold layer while using the BI platform primarily to visualize, analyze, and consume trusted data.

With the Gold layer serving as the analytics foundation, the next step is to consider what capabilities a BI platform should provide.

Factors to Consider When Choosing a BI Platform

Choosing a BI platform involves more than simply connecting to data. The platform should support current analytics requirements while providing flexibility to scale as data volumes, users, and business needs grow.

When evaluating a BI platform, consider:

• Data connectivity: Support for the databases, lakehouses, data warehouses, and cloud platforms hosting Gold-layer datasets.
• Performance and scalability: Ability to support growing datasets, users, dashboards, and analytics workloads.
• Self-service analytics: Tools that allow business users to explore and analyze trusted data independently.
• Governance and security: Capabilities such as role-based access control, authentication, auditing, and compliance support.
• Embedded analytics: Ability to integrate dashboards and analytics into applications, portals, and customer-facing products.
• Developer and SDK capabilities: Evaluate how quickly dashboards can be integrated into customer-facing applications, SaaS products, business portals, and internal systems without extensive custom development.
• Customization and extensibility: Flexibility to customize dashboards, branding, integrations, and analytics experiences.
• Deployment options: Support for cloud, on-premises, and hybrid environments.
• Cost and maintainability: Licensing, infrastructure, administration, and long-term ownership requirements.
• Pricing scalability: Consider whether the platform uses per-user licensing or a pricing model that supports organization-wide deployment and embedded analytics growth without unpredictable licensing costs.

The right BI platform should complement the Gold layer rather than replace it, consuming trusted data while providing the analytics capabilities needed by business users and applications.

Next, let's look at how Bold BI works with Medallion Architecture Gold-layer data.

Why Bold BI Is a Strong Choice for Medallion Architecture Gold-Layer Analytics

Organizations that invest in a Medallion Architecture already have trusted, business-ready data available in their Gold layer. The next challenge is making that data accessible through dashboards, self-service analytics, and embedded analytics applications without recreating business logic or building analytics infrastructure from scratch.

Bold BI helps organizations unlock the value of their Gold-layer investments by connecting directly to certified datasets while preserving the KPI definitions, governance controls, and business rules already established within the data platform.

Key Benefits of Connecting Bold BI to Gold-Layer Data

• Connect to 140+ data sources including Databricks, Snowflake, Microsoft Fabric, Azure Synapse Analytics, SQL Server, PostgreSQL, and many other analytics platforms.
• Preserve a single source of truth by consuming certified Gold-layer datasets rather than recreating calculations and KPI definitions inside dashboards.
• Accelerate time-to-value by building dashboards and analytics experiences on top of existing Gold-layer assets instead of spending months developing custom analytics frameworks.
• Embed analytics anywhere using Bold BI's SDKs and APIs to integrate dashboards into SaaS applications, customer portals, and internal business systems.
• Deploy on your terms with cloud, self-hosted, and hybrid deployment options that support data residency, governance, and compliance requirements.
• Scale predictably with flat pricing that helps organizations expand analytics usage without the complexity of per-user licensing costs.
• Enable self-service analytics so business users can explore trusted Gold-layer data while maintaining centralized governance and KPI consistency.

By connecting Bold BI directly to Gold-layer assets, organizations can deliver governed analytics experiences while maintaining a centralized source of truth across dashboard, embedded applications, and operational workflows.

Next, let's explore how to connect Medallion Architecture Gold-layer data to Bold BI.

How to Connect Bold BI to a Medallion Architecture Gold Layer

Once a Gold layer exists, connecting Bold BI to it is a standard data connection, not a special integration:

Step 1: Identify the Gold-layer data source

Start by confirming where your Gold-layer datasets live. This is typically a platform like Databricks SQL, Snowflake, Microsoft Fabric Lakehouse, Azure Synapse, SQL Server, PostgreSQL, or another supported analytics platform.

Step 2: Create a data connection in Bold BI

In the Bold BI Dashboard Designer, create a new data source and select the connector that matches your Gold-layer platform. Enter your credentials in the data source configuration panel to complete the connection. In this example, we'll use the Snowflake connector.

Step 3: Select certified Gold-layer assets

From the pop-up window, choose the approved fact tables, dimension tables, KPI tables, semantic models, analytics views, or data marts you want to bring into your dashboard.

Step 4: Build dashboards and analytics experiences

Click Continue to Dashboard to open the dashboard designer. From here, use your Gold-layer data to create your dashboard or scorecards tailored to your analytics needs.

Step 5: Configure refresh schedules

Keep your dashboard current by scheduling dataset refreshes so it always reflects the latest approved data. The GIF below walks through scheduling a refresh for Snowflake data.

Step 6: Deliver trusted insights to users

Click Publish and confirm by selecting Yes to make the dashboard available to business users. Because it's built on curated Gold-layer data, everyone works from the same trusted, consistent source of truth.

Use Case: Embedded Analytics on Gold-Layer Data

Embedded analytics helps organizations extend the value of Gold-layer datasets across IT operations. The Snowflake usage analytics dashboard shows how certified Snowflake usage data can power consistent analytics experiences with Bold BI.

• Scenario: IT teams want to embed Snowflake usage analytics into internal portals to monitor warehouse activity, query performance, storage usage, and user activity.
• Challenge: Different teams often create separate monitoring dashboards, resulting in inconsistent metrics and duplicated effort.
• How Bold BI addresses it: Bold BI connects to certified Gold-layer datasets, ensuring all embedded dashboards use the same trusted Snowflake usage metrics and KPIs.
• Business outcome: IT teams gain consistent visibility into platform usage and performance, improve governance, and reduce analytics complexity.

Because the Gold layer centralizes usage metrics and business rules, every embedded dashboard delivers a consistent and trusted view of Snowflake operations across the organization.

By combining the Medallion Architecture Gold layer with Bold BI, organizations can deliver reliable, embedded analytics without duplicating business logic across dashboards.

Ready to Connect Bold BI to Your Gold Layer?

The value of the Gold layer extends far beyond cleaner data. Organizations that connect Bold BI® to a Gold layer gain access to trusted datasets, standardized KPI definitions, improved governance, and faster analytics delivery across dashboards, and embedded applications.

By connecting Bold BI directly to Gold-layer datasets, organizations can improve dashboard performance, strengthen governance, and deliver consistent analytics experiences without duplicating business logic across teams.

Ready to put your Gold-layer data to work? Bold BI connects to more than 140 data sources, including Databricks, Microsoft Fabric, Snowflake, Azure Synapse Analytics, SQL Server, and PostgreSQL, making it easy to transform certified Gold-layer datasets into dashboards, self-service analytics, and embedded analytics experiences. Explore our integration documentation to learn more about supported connectors and platforms.

Start a free trial to explore Bold BI with your own datasets or schedule a personalized demo to see how Bold BI helps organizations turn trusted Gold-layer data into actionable insights across dashboards and embedded applications.

Frequently Asked Questions

1. 1. What is the Gold layer in Medallion Architecture?

      The Gold layer is the final, business-ready stage of Medallion Architecture where KPI definitions, fact tables, dimension tables, and semantic models are standardized for analytics consumption.

   2. How do you connect Bold BI to a Gold layer?

      To connect Bold BI to a Gold layer, create a data connection to the platform hosting the Gold-layer datasets, such as Databricks, Snowflake, Microsoft Fabric, Azure Synapse, SQL Server, or PostgreSQL. After connecting, select certified Gold-layer assets, build dashboards, configure refresh schedules, and publish analytics experiences using trusted business-ready data.

   3. Why should BI platforms connect to the Gold layer instead of the Silver layer?

      The Gold layer contains approved KPI definitions, business rules, semantic models, and curated analytical structures. Connecting Bold BI directly to the Gold layer helps maintain a single source of truth, reduce duplicated calculations, strengthen governance, and improve consistency across dashboards, and analytics applications.

   4. Can Bold BI create Gold-layer datasets?

      Bold BI supports dataset shaping through calculated fields, expressions, relationships, filtering, and custom queries. However, enterprise-scale Gold-layer creation should occur within platforms such as Databricks, Microsoft Fabric, Snowflake, or Azure Synapse.

   5. Does Bronze-to-Silver processing happen inside Bold BI?

      No. Data cleansing, validation, standardization, deduplication, and quality management belong in the underlying data platform. Bold BI focuses on analytics consumption after those processes are complete.

   6. What transformations can Bold BI perform?

      Bold BI supports calculated fields, expressions, relationships, custom queries, filtering, extract mode, scheduled refreshes, and presentation-level formatting functions, helping analytics teams work with Gold-layer datasets.

   7. Why does the Gold layer matter for embedded analytics?

      Embedded analytics applications depend on consistent KPI definitions and responsive performance. Gold-layer datasets provide standardized business logic to ensure that every embedded dashboard delivers the same trusted metrics to every user.