Introducing Snowplow Data Quality Dashboard

A New Era of Data Quality Monitoring

Ensuring high-quality behavioral data is at the core of Snowplow's mission. While our schema validation framework helps prevent bad data from entering your pipeline, identifying and resolving tracking issues has historically been a fragmented process. 

Today, we are excited to introduce the Data Quality Dashboard—a powerful new tool designed to help you quickly detect, diagnose, and fix failed events, all within the Snowplow Console.

With this dashboard, your browser connects securely to an API running within your infrastructure, acting as a simple proxy to retrieve failed event data from your warehouse. This means you get full transparency into data quality issues while maintaining complete control over your data. The connection is fully encrypted (HTTPS) and uses the same authentication and authorization mechanisms as the Snowplow Console, ensuring security and compliance.

To get started, you’ll need to sink failed events to your warehouse using a Failed Events Loader. Currently, the Data Quality Dashboard supports Snowflake, with support for Databricks and BigQuery coming soon.

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Why We Built the Data Quality Dashboard

Maintaining data integrity is a persistent industry challenge. Common issues include:

• High noise in error reporting: many platforms generate excessive, non-specific alerts, making it difficult to identify critical issues.
• Limited prioritization options: Not all data errors are equal—some tracking failures have a greater impact on business decisions than others.
• Lack of actionable insights: Many solutions provide failure summaries but fail to surface detailed information that would enable quick debugging.
• Inefficient workflows: Resolving tracking errors often requires collaboration across multiple teams and tools, slowing down response times.

Snowplow’s previous Failed Events UI was no exception to these rules. However we have recently released Failed Events Loaders that load raw failed events directly to the warehouse in a similar format to atomic events, making it the perfect time to improve our Console experience as well.

Key Features

The Data Quality dashboard provides a streamlined and powerful interface for tracking quality management. Key capabilities include:

1. Centralized Interactive Dashboard

A new Data Quality tab in the Snowplow Console provides a comprehensive view of failed events, making it easy to monitor tracking health across your application estate. Users can now see summaries of failed events in much greater detail.

• Volume of failures over time
• Breakdown by event name, error type, and affected properties
• Trends to track improvements or emerging issues

2. App Version Tracking

Failed events are often introduced in new builds of your app that cause silent regression issues. Alongside our existing mobile application entity, we have added an app version that you can use to record the current version of your web and server-side apps, making it easier to trace the source of the error. Our dashboard will display this field (coalesced with the Mobile AppVersion) for easier debugging.

3. Detailed Event Diagnostics

For the first time, Snowplow customers can inspect individual failed events, including:

• Full event payloads
• Schema and tracker details
• Precise error messages and suggested fixes

4. Customizable Filtering and Prioritization

Teams can filter failed events by key attributes (event type, app version, error type, etc.), helping them focus on business-critical tracking issues first.

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Get Started

The Data Quality Dashboard is rolling out now in Snowplow Console and you can find it in the Failed Events tab (the old UI is still available if you would like to switch back).

For more details, visit our documentation or reach out to our team for a demo.

With the Data Quality Dashboard, we’re making it easier than ever for teams to detect, diagnose, and resolve tracking issues—so they can trust their behavioral data from the start.