Anomalo Partners With dbt Labs to Bring Data Quality to Key Business Metrics

Anomalo Partners With dbt Labs to Bring Data Quality to Key Business Metrics

Today at Coalesce, Anomalo, the complete data quality platform company, announced a partnership with dbt Labs to provide data quality for dbt metrics, a part of the new dbt Semantic Layer. Anomalo is now a Metrics Ready Launch Partner of dbt Labs.

dbt is a transformation framework that enables businesses to transform, test and document data in the cloud data platform, producing data that the entire organization can trust. With the launch of dbt metrics and the dbt Semantic Layer, organizations can now centrally define key business metrics like ‘revenue,’ ‘customer count’ and ‘churn rate’ in dbt. This allows everyone in the business to feel confident that they are working from the same assumptions as their colleagues, regardless of their data tooling of choice. If a metric definition is updated in dbt, it is seamlessly updated everywhere, ensuring consistency throughout the business. Metrics Ready integrations facilitate the building, discovery and reliability of dbt metrics definitions.

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As a Metrics Ready Launch Partner, Anomalo will now automatically start monitoring metrics that are defined in the dbt Semantic Layer. When a joint customer monitors a dbt model in Anomalo, Anomalo’s Key Metric checks and default built-in data quality checks will monitor for any drift in the data that feeds dbt metrics. Key Metric checks are an important piece of Anomalo’s data quality platform, and allow customers to track any business metrics in Anomalo and be notified when metrics have changed dramatically. All Key Metrics checks include interactive visualizations to allow for a fast assessment and resolution of any anomalies. Metric definitions are synced and consistent between the dbt Semantic Layer and Anomalo.

When the metrics that a company relies on are universal and centrally defined, it is even more important that they are based on trustworthy data. Anomalo helps teams operate with confidence and understand the root cause when deviations in their metrics occur, so they can find any data quality issues before they affect dashboards and reports and separate any data quality issues from the meaningful trends in their data.

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Cameron Afzal, product manager for the Semantic Layer at dbt Labs, said: “We’re excited to partner with Anomalo to help customers proactively monitor the reliability of dbt metrics they’re querying using the dbt Semantic Layer. Anomalo’s data quality monitoring solution automatically detects data issues related to dbt metrics and allows data teams to understand their root causes before they impact downstream tools, meaning everyone in the business can operate with more confidence.”

Elliot Shmukler, co-founder and CEO of Anomalo, said: “We are always eager to contribute to solutions that improve the data ecosystem for all users, and partnering with dbt was an easy decision. As the dbt Semantic Layer enables ‘define once, use everywhere’ business metrics, it’s critical that there is observability and monitoring for this central source of truth. Joint customers using Anomalo and dbt can now easily define and monitor metrics end-to-end to power data-driven decisions that everyone at the organization can trust.”

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