How to Connect Snowflake Data to BI Dashboard

TL;DR: Building a dashboard with Snowflake data in Bold BI® makes it easier to turn cloud data into real-time, interactive insights without unnecessary complexity. With a direct connection to Snowflake, Bold BI helps teams visualize key metrics, monitor performance, and make faster data-driven decisions through secure and scalable dashboards.

Introduction

As more organizations adopt cloud data platforms such as Snowflake, many teams look for efficient ways to access and visualize their data. Snowflake offers scalable storage and processing, but turning raw data into shareable dashboards may still require the right analytics tool.

Dashboarding tools like Bold BI can help by providing a web-based environment to connect to Snowflake, visualize data, and explore metrics through interactive dashboards. By integrating snowflake with Bold BI, teams can monitor key metrics, analyze trends, and share insights with stakeholders. This guide walks through connecting to Snowflake, preparing data, and building a dashboard in Bold BI to support more consistent, accessible reporting.

What is Snowflake?

Snowflake is a cloud-based data platform designed to store, process, and analyze large volumes of structured and semi-structured data. Built for scalability and performance, it enables organizations to manage data workloads efficiently without the limitations of traditional data warehouses.

Benefits of integrating Snowflake data into a BI platform

Integrating Snowflake with a BI platform can help organizations make better use of their cloud data by improving accessibility and visualization:

• Improved data accessibility: Connecting Snowflake to a BI platform allows users to access and explore data through visual interfaces instead of relying only on complex queries.
• Centralized data visualization: Integrating with Snowflake helps consolidate data into a single reporting layer, which can improve consistency and reduce fragmentation.
• Scalable analytics: Since Snowflake is designed for scalable data storage and processing, BI platforms can leverage this to handle growing data volumes and user demands.
• Real-time analytics: Many BI platforms support direct connections to Snowflake, which can help provide more up-to-date insights compared to manual reporting methods.
• Enhanced collaboration and sharing: BI tools make it easier to share dashboards and reports across teams, helping stakeholders access the same information in a structured format.
• Data-driven decision-making: By combining Snowflake’s data capabilities with BI visualizations, organizations can improve visibility into key metrics and support more informed decisions.

How to Connect Snowflake Data to Bold BI Dashboard

Connecting Snowflake to a BI dashboard can be tricky, but Bold BI simplifies it with an intuitive setup flow. Follow the steps below or refer to the Bold BI help documentation to configure your Snowflake data correctly.

Before you start:

Make sure you have the following details from your Snowflake account:

• Account URL
• Warehouse name
• Database and schema
• Username and password (or key‑based credentials)

You’ll also need access to Bold BI (cloud or embedded versions).

Step 1: Open the Bold BI dashboard Designer

Log in to the Bold BI dashboard page. From the left-hand navigation panel, click Data Sources to open the data source management page.

Step 2: Create a new data source

In the Data Sources page, click New Data Source in the top-right corner. From the dropdown menu, select Create Data Source. This opens the data source selection panel listing all supported connectors.

Step 3: Select Snowflake connector

On the Connection panel, select Snowflake connector option.

Step 4: Enter Snowflake connection details

The Snowflake data connection window will open in the data source configuration page as shown. Here, enter a Name for the data source and, optionally, a description. Specify the Server Name (Snowflake account URL), choose the Authentication Mechanism, and enter the UserName and Password. Next, select the required Mode (Live or Extract) and provide the Database name.
After entering all the details, click Connect to establish the connection.

Step 5: Load Snowflake Schemas in the Data Source Designer

After a successful connection, the Data Source Designer opens automatically. All available Snowflake schemas, such as INFORMATION_SCHEMA and PUBLIC, are loaded and displayed in the left panel as shown.

Step 6: Select tables from Snowflake schema

Here, expand INFORMATION_SCHEMA from the left panel. You will see a list of options, such as Tables. Expand Tables, then expand Views that appears inside it.

Step 7: Select a view, drag and drop, and preview data

Select a view from the list shown in the left panel. Drag the selected view into the design area, where the column details are displayed. Click Data Preview, as shown in the image, and verify that the records are loaded correctly.

Step 8: Save the data source

After verifying the data preview, click the more options (☰) icon in the top‑right corner of the data source designer. From the menu, you can choose Code to switch to Code mode and view or edit the generated query. To complete the process, click Save and Exit to save the Snowflake data source and close the designer.

Alternatively, select Continue to Dashboard to proceed directly to dashboard creation.

With your data source configured, the next step is turning Snowflake data into meaningful dashboards. Let's explore how you can achieve this with Bold BI

Creating a dashboard using Snowflake data in Bold BI

Using the data loaded from Snowflake, you can define metrics and KPIs to create a Snowflake usage analytics dashboard that provides clear visibility into warehouse activity, query behavior, and credit consumption. The following metrics can be used to build an interactive dashboard:

• Total users: showing the number of active Snowflake users.
• Total databases: indicating database availability and usage scope.
• Query success rate: measuring successful query execution percentage.
• Average elapsed query time: reflecting overall query latency.
• Average execution time: highlighting query performance efficiency.
• Total credits used: tracking overall compute consumption.

To analyze usage patterns and cost distribution in greater detail, the dashboard can also include:

• Query amount by type: such as SELECT, CREATE, ALTER, and SHOW queries.
• User numbers by database: showing how users are distributed across databases.
• Top warehouses by credit usage: identifying high‑consumption warehouses.
• Top warehouses by compute cost: supporting cost monitoring and optimization.
• Total users and query volume by warehouse: comparing workload distribution across warehouses

A Snowflake usage analytics dashboard enables data platform and operations teams to monitor performance trends, detect unusual usage spikes, optimize warehouse utilization, and control Snowflake costs, all through a single, interactive dashboard created in Bold BI.

Real-world use case of visualizing snowflake data

The following are some use cases of a Snowflake dashboard.

Warehouse cost optimization

A data engineering manager notices a sudden spike in Snowflake costs but struggles to pinpoint which warehouse is driving the increase. Analyzing multiple reports manually takes time and delays cost-control decisions.

Using the dashboard, the manager can quickly view top warehouses by compute cost and credit usage. In the example widget, production shows the highest cost ($8.7K) and credit usage (1.12K), making it easy to identify optimization opportunities, such as resizing or auto-suspending warehouses.

Workload analysis by query type

A data platform owner wants to understand whether Snowflake is being used more for analytics or schema operations but has no clear breakdown of query types.

With the query count by type widget, the dashboard shows a dominance of SELECT queries (38), indicating heavy analytical usage. This helps in deciding workload isolation strategies, such as separating ETL and reporting workloads into different warehouses.

User activity and data adoption tracking

A data leader wants to know which datasets are actively used and which are underutilized to guide data investment decisions.

The user count by database visual reveals which databases are most accessed. This enables teams to prioritize high-value datasets and deprecate unused ones.

Scheduling Snowflake data refresh in Bold BI

Bold BI lets you schedule refresh for datasets and dashboards that use Snowflake data so your analytics stay up to date automatically at the time you choose.

You can automate Snowflake data refresh on a daily, weekly, or monthly basis (or set custom intervals), ensuring snowflake dashboards and reports consistently display the latest data without manual refresh. Bold BI also supports failure notifications, so you can be alerted if a scheduled refresh doesn’t complete successfully. To configure scheduling, follow the step-by-step guide in our documentation or the steps shown in the following GIF.

Collaborating and sharing Snowflake insights in Bold BI

To collaborate and share insights from your Snowflake dashboards in Bold BI, follow these steps or refer to the official documentation.

Step 1: Open the dashboards listing page

Log in to Bold BI Dashboards page, using your preferred login method and then click a Share option in the dashboard listing page.

[caption id="" align="alignnone" width="1484"] Open the dashboards listing page and click the share icon[/caption]

Step 2: Review the dashboard options

When the Share with others dialog opens, review the dashboard’s sharing details:

• The current visibility is shown as private, meaning only users with explicit permissions can access the dashboard.
• Click Change to modify the visibility if needed.
• Click Copy link to copy the dashboard URL for sharing.
• View the list of users or groups with whom the dashboard is already shared.
• Click Manage Access to review or update existing permissions.

[caption id="" align="alignnone" width="1484"] Review the dashboard options[/caption]

Step 3: Add users or groups

In the Share with others dialog, use the search field to find and select the required user or group. Open the permission dropdown and assign the appropriate access level: Read; Read and Write; Read, Write, and Delete; or Download. In my case, I select Read access.

[caption id="" align="alignnone" width="1484"] Add users and select access option[/caption]

Step 4: Apply sharing permissions

After adding the required users or groups and assigning the appropriate permission level, click Share to apply the sharing settings. Once the access has been successfully applied, click Done to close the dialog. The selected users or groups will now have access to the dashboard according to the permissions granted.

[caption id="" align="alignnone" width="1484"] Click Share[/caption]

[caption id="" align="alignnone" width="1484"] Click Done[/caption]

Users with access to the dashboard can collaborate by:

• Adding comments at the dashboard or widget level.
• Replying to existing comments.
• Mentioning others using @username.

Comments help teams discuss insights directly within Bold BI without using external communication tools. For more details about collaboration in Bold BI, refer to our blog on What Is Collaborative BI and How Does It Work? or collaborative analytics page.

Transform Snowflake data into business insights

Snowflake gives you a powerful, scalable foundation for analytics, but real value comes when stakeholders can see, explore, and act on that data without friction. By connecting Snowflake to Bold BI®, teams can convert warehouse data into interactive dashboards that update automatically, follow governance rules, and scale with business needs.

Whether you’re monitoring usage trends, analyzing operational performance, or delivering metrics to internal teams or customers, Bold BI helps you move from raw Snowflake tables to decision‑ready analytics, faster and with less effort.

Ready to turn your Snowflake data into dashboards your teams actually use? Start your free trial today or explore our live demo to experience how Snowflake data can be visualized and analyzed in Bold BI. Additionally, if you’re evaluating options, don’t miss our guide on the Top 5 Dashboarding Tools to Explore for Snowflake in 2025 to discover the best fit for your needs.

Frequently asked questions

1. 1.

   Does Bold BI support real-time Snowflake data?

   Bold BI supports updates from Snowflake through scheduled refresh. For the most up-to-date results, use live mode (querying Snowflake at runtime) where appropriate.
2. 2.

   Can I use Snowflake tables and custom SQL?

   Yes. You can connect using Snowflake tables, views, or custom SQL queries when creating the data source.
3. 3.

   How is performance handled for large Snowflake datasets?

   All features work seamlessly in embedded environments.
4. 4.

   Does chart switching work in embedded mode?

   For large datasets, use extract mode to cache data for faster dashboard load times and to reduce repeated queries to Snowflake.
5. 5.

   Is Snowflake data secure in Bold BI?

   Yes. Bold BI respects Snowflake authentication and roles while applying its own access controls for dashboards and users.