How to Build a Snowflake Credit Usage Dashboard (SQL)

16 minutes to read

October 31, 2025

Are you finding it difficult to monitor rising Snowflake costs, or to attribute credit usage to specific teams, projects, or business units? This step-by-step guide delivers hands-on SQL recipes designed for BI developers and FinOps analysts to build a transparent, actionable Snowflake credit usage dashboard. With these tools, you can evolve from manual reporting to streamlined, automated financial control—while laying a foundation for effective FinOps practice.

As data architects, these are the same foundational queries we use at Stellans to help our clients manage millions in annual Snowflake spend and build effective FinOps practices.

Looking for next-level warehouse automation? See our Automate Snowflake Warehouse Scaling with Resource Monitors guide for proven automation techniques.

Why Manually Monitoring Snowflake Spend is a Good First Step

Before investing in complex Snowflake FinOps tools, setting up a manual Snowflake credit usage dashboard gives both technical and financial teams much-needed visibility and accountability.

Immediate transparency: Manual dashboards let you visualize daily and monthly Snowflake spend using simple SQL, giving fast feedback before budgets spiral.
No new software required: Anyone with access can start tracking costs without added vendors. This is especially practical for organizations in the early stages of their FinOps journey.
Empowers better decision-making: Identifying high-spend warehouses, inefficient queries, and misuse helps teams address issues quickly with data-backed evidence.
Facilitates showback/chargeback: Granular, traceable tracking lays the groundwork for mapping Snowflake spend to business units or projects, paving the way for reliable showback models.
Hands-on FinOps learning: Writing SQL to explore METERING_HISTORY and WAREHOUSE_METERING_HISTORY teaches essential cost management skills before moving to automated tools like the Stellans FinOps Dashboard.

Manual dashboards provide actionable insights—helping you control spend before scaling up.

The Foundation: Querying ACCOUNT_USAGE for Granular Cost Data

The Snowflake ACCOUNT_USAGE schema is the definitive source for detailed cost data. Starting with ACCOUNT_USAGE ensures a unified, audit-friendly view of your organization’s spend.

Extensive visibility: ACCOUNT_USAGE includes compute, storage, and cloud services usage, encompassing data at every level—from account-wide rollups to individual users or query tags.
Granularity for cost attribution: Unique fields make it possible to drill into usage by warehouse, user, role, or even query tag.
Multi-account support: For organizations with multiple Snowflake accounts, combining ACCOUNT_USAGE with ORGANIZATION_USAGE facilitates aggregated oversight across your cloud estate.
Integration-ready: Queries in ACCOUNT_USAGE can be used directly within BI tools, such as Tableau, Power BI, and Looker, with no vendor lock-in. This enables flexible dashboarding, a key competitive advantage over native or single-tool options.

Solid cost attribution from these tables enables showback and chargeback practices aligned to the FinOps Foundation framework. Supporting regulatory or audit requirements is also easier via retained historical usage detail.

Key Views for Cost Monitoring: METERING_HISTORY & WAREHOUSE_METERING_HISTORY

The backbone of Snowflake credit usage monitoring relies on two key views:

METERING_HISTORY: Summarizes credits consumed at the account or organization level, ideal for trending and policy checks.
WAREHOUSE_METERING_HISTORY: Reports credit usage by each compute warehouse, with detailed time breakdowns for active and suspended periods. This enables cost mapping to projects or teams.

For organizations using multiple Snowflake accounts, you can aggregate data for broad oversight using ORGANIZATION_USAGE. Consult ACCOUNT_USAGE documentation for field details and schema updates.

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Actionable SQL Recipes for Your Snowflake Credit Usage Dashboard

Production-ready SQL is all you need to power a credible Snowflake cost monitoring dashboard—no extra software or plugins required. Here are three essential queries any monitoring dashboard should include:

Recipe 1: Track Daily & Monthly Credit Usage by Compute Warehouse

Monitoring usage by warehouse helps identify high-spend teams or workloads and pinpoints spend spikes before they become major issues. This recipe leverages WAREHOUSE_METERING_HISTORY, which now provides retention of up to 1 year of data for Snowflake Standard Edition customers or longer for Enterprise.

Sample SQL:

SELECT
  warehouse_name,
  DATE(start_time) AS usage_date,
  SUM(credits_used) AS daily_credits
FROM
  SNOWFLAKE.ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY
WHERE
  start_time >= DATEADD(month, -3, CURRENT_DATE)
GROUP BY
  warehouse_name, DATE(start_time)
ORDER BY
  warehouse_name, usage_date DESC;

How this helps:

Highlights which warehouses or workloads are driving overall spend.
Flags irregular spikes or increases in credit use, supporting set baseline budgets.
Simplifies the creation of team- or project-level dashboards through warehouse-to-business mapping.

Monthly reporting can be achieved by swapping usage_date for MONTH(start_time) or via your BI tool’s date groupings.

Recipe 2: Identify and Attribute High-Cost Queries to Users or Roles

With modern ELT and analytics workloads, a handful of queries can account for a large part of your spend. Finding and attributing these is key to technical tuning and fair cost governance. By joining QUERY_HISTORY with user and role metadata, you unlock deep insights for FinOps.

Sample SQL:

SELECT
  user_name,
  role_name,
  query_text,
  credits_used_compute + credits_used_cloud_services AS total_credits,
  execution_status,
  start_time
FROM
  SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY
WHERE
  start_time >= DATEADD(day, -14, CURRENT_DATE)
  AND total_credits > 0
ORDER BY
  total_credits DESC
LIMIT 50;

How this helps:

Surfaces costly queries, ranked by actual credit consumption—not just runtime.
Enables targeted refactoring or scheduling changes for expensive workloads.
With consistent use of query tagging, enables attribution to projects or departments for showback/chargeback.

This approach not only flags issues but ties cost back to business units for accountability.

Recipe 3: Analyze Storage Costs Over Time

While compute drives variable spend, storage costs can accumulate quietly. With the STORAGE_USAGE view, you can investigate storage trends and support retention policy decisions.

Sample SQL:

SELECT
  TO_DATE(usage_date) AS storage_date,
  SUM(stage_bytes + failsafe_bytes + table_bytes) / 1e9 AS total_storage_GB
FROM
  SNOWFLAKE.ACCOUNT_USAGE.STORAGE_USAGE
WHERE
  usage_date >= DATEADD(month, -6, CURRENT_DATE)
GROUP BY
  TO_DATE(usage_date)
ORDER BY
  storage_date DESC;

How this helps:

Tracks storage use as a trend, identifying costly jumps (such as when failsafe or transient tables aren’t purged)
Informs archiving or cleanup policies—one of the fastest wins for Snowflake cost optimization
Demonstrates compliance with retention or audit requirements

Visualizing Your Data: From Queries to Dashboards

Running these SQL queries is only the first step—integrating their results into dashboards provides continuous, actionable insight.

Flexible charting: Visualize daily, weekly, and monthly credits by warehouse, user, or project using BI tools such as Tableau, Power BI, or Looker.
Highlight problem areas: Use charts like stacked bars or heatmaps to isolate large spikes or identify where cost drivers are concentrated.
Encourage data-driven collaboration: Share dashboards with technical teams, budget owners, and leadership for proactive conversations rather than reactive investigations.

Snowflake natively supports direct connections for these BI platforms. For concrete dashboard examples and best practices, see ACCOUNT_USAGE schema docs or our quick Snowflake cost alerts guide.

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The Limits of Manual SQL-Based Monitoring

Manual SQL dashboards are invaluable early on, but you’ll eventually encounter real-world limitations:

Ongoing maintenance: As users, warehouses, and business units grow, updating queries and wrangling data mappings becomes both complex and error-prone.
Delayed visibility: Manual reporting often leads to budget overruns being detected after thresholds are crossed, rather than in real time.
Scaling challenges: Attribution and split-by-team reporting is harder to maintain as your organization or Snowflake usage grows, especially in multi-account environments.
No policy enforcement: Manual solutions don’t automate governance or compliance (for example, disabling warehouses at budget limits); this requires built-in enforcement like Snowflake Resource Monitors.
Fragmented reporting: Without a unified source of truth, conflicting numbers can lead to spend disputes between IT, finance, and engineering.

When these issues arise, it’s time to shift from spreadsheets and static dashboards to automated FinOps solutions.

Next Step: From Manual Reports to Automated FinOps Governance with Stellans

For organizations that have outgrown manual dashboards, an automated, unified Snowflake FinOps solution offers game-changing benefits:

Benefits of Automated Snowflake FinOps with Stellans

Real-time credit usage alerts: Get notified instantly—across all accounts—of emerging overruns, costly trends, or unusual activity, before budgets are exceeded.
Automated showback and chargeback: Link Snowflake credit use to business units, product lines, or cost centers, with mappings updated automatically and supported by audit trails.
Built-in governance and enforcement: Use policy-driven rules to suspend or restrict usage automatically when thresholds are reached (leveraging the latest Resource Monitor and Budget features).
Comprehensive analytics: Drill down by user, warehouse, query tag, or account—even across multiple Snowflake environments.
Unified, collaborative workspace: Give FinOps, engineering, and business leaders shared dashboards, facilitating informed decisions and reducing time spent on manual reconciliation.
Continual innovation: Stellans supports seamless integration as Snowflake releases improvements (like enhanced ORGANIZATION_USAGE for cross-account rollups and new compliance guardrails).

Ready to automate Snowflake credit usage monitoring? Request a Stellans demo and put your FinOps on autopilot.

Manual dashboards are a strong starting point, but unlocking true governance, scalability, and audit compliance calls for dedicated automation. Stellans bridges the gap—giving your technical and financial teams the confidence to control spend as you grow.

Frequently Asked Questions (FAQ)

How do you set up credit usage alerts in Snowflake?

To stay ahead of budget overruns, use Resource Monitors to define credit usage thresholds by account or warehouse. You can configure actions like notifications or automatic suspension when predefined limits (such as 80% and 95%) are reached. Best practice is to attach Resource Monitors to all production warehouses and set multiple thresholds to avoid disruption and enable proactive cost management.

For an illustrated walkthrough, see our step-by-step cost alert guide.

What is the difference between Snowflake Resource Monitors and Budgets?

Resource Monitors are technical control tools that can act directly—such as suspending a warehouse or notifying when a credit threshold is reached. Budgets, currently in preview, focus on monitoring and notifying without direct enforcement. Budgets are best for tracking and alerting across Snowflake objects (warehouses, databases, etc.) to support financial oversight and compliance.

Resource Monitors: Enforce spend limits with technical actions; ideal for automated governance.
Budgets: Enable broader monitoring and alerts, supporting financial planning, but do not suspend workloads.

Both are essential: Resource Monitors help control risk, while Budgets provide cross-account financial visibility.

Article By:

https://stellans.io/wp-content/uploads/2024/09/DavidStellans2-1-2.png

David Ashirov

Co-founder and CTO of Stellans

Get free consultation

How to Build a Snowflake Credit Usage Dashboard (SQL)

Why Manually Monitoring Snowflake Spend is a Good First Step

The Foundation: Querying ACCOUNT_USAGE for Granular Cost Data

Key Views for Cost Monitoring: METERING_HISTORY & WAREHOUSE_METERING_HISTORY

Actionable SQL Recipes for Your Snowflake Credit Usage Dashboard

Recipe 1: Track Daily & Monthly Credit Usage by Compute Warehouse

Recipe 2: Identify and Attribute High-Cost Queries to Users or Roles

Recipe 3: Analyze Storage Costs Over Time

Visualizing Your Data: From Queries to Dashboards

The Limits of Manual SQL-Based Monitoring

Next Step: From Manual Reports to Automated FinOps Governance with Stellans

Benefits of Automated Snowflake FinOps with Stellans

Frequently Asked Questions (FAQ)

How do you set up credit usage alerts in Snowflake?

What is the difference between Snowflake Resource Monitors and Budgets?

Article By:

David Ashirov

Related Posts

Let’s
Talk

Get a Free Data Audit

How to Build a Snowflake Credit Usage Dashboard (SQL)

Why Manually Monitoring Snowflake Spend is a Good First Step

The Foundation: Querying ACCOUNT_USAGE for Granular Cost Data

Key Views for Cost Monitoring: METERING_HISTORY & WAREHOUSE_METERING_HISTORY

Actionable SQL Recipes for Your Snowflake Credit Usage Dashboard

Recipe 1: Track Daily & Monthly Credit Usage by Compute Warehouse

Recipe 2: Identify and Attribute High-Cost Queries to Users or Roles

Recipe 3: Analyze Storage Costs Over Time

Visualizing Your Data: From Queries to Dashboards

The Limits of Manual SQL-Based Monitoring

Next Step: From Manual Reports to Automated FinOps Governance with Stellans

Benefits of Automated Snowflake FinOps with Stellans

Frequently Asked Questions (FAQ)

How do you set up credit usage alerts in Snowflake?

What is the difference between Snowflake Resource Monitors and Budgets?

Article By:

David Ashirov

Related Posts

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