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If the consequences of data issues are high

If you are running performance marketing budgets of $millions, a data issue can result in a loss of hundreds of thousands of dollars. In these cases, the ability to detect and resolve issues fast is business-critical. It typically involves multiple teams and the ability to measure, track, and report on data quality.

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If data is scaling faster than the data team

The scale and complexity of modern data environments make it impossible for teams to manually manage quality without expanding the team. A data observability platform enables automation and collaboration, ensuring data quality is maintained as data continues to grow, without impacting team efficiency.

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Common use cases

If your data is being used in one of the following use cases, you should consider adding a data observability platform:

  • Self-service analytics
  • Data activation
  • Powering AI & ML products
  • Embedded analytics
  • Performance marketing
  • Regulatory reporting
  • A/B testing and experiments

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Why isn’t the open-source package enough?

The open-source package was designed for engineers that want to monitor their dbt project. The Cloud Platform was designed to support the complex, multifaceted requirements of larger teams and organizations, providing a holistic observability solution.

Webhooks (Beta)Cloud vs OSS