- Anomalo provides a solution that we can easily integrate with our data stores (Snowflake, Databricks Delta) and immediately start to configure data quality checks for all the tables that we care about. - Anomalo in general is very easy to use, yet it is also comprehensive. It allows us to configure almost any key metrics and validation rules in SQL based on what we need to monitor for data quality. It provides integration with Okta, Slack, PagerDuty which are the tech stacks that we use in Opendoor, therefore onboarding Anomalo is quite a smooth experience. - In addition to the UI, Anomalo also provides a Python SDK which enables a ton of flexibility to integrate Anomalo into building data pipelines and triggering data quality checks on the fly. - Anomalo's team has been quite responsive to our questions and requests. We have regular office hours to meet with Anomalo's team to discuss questions and so far it has been very helpful every time.

Automated anomaly detection makes my life as a data engineering professional way easier, especially managing high-visibility datasets where important failures are not just a matter of the ETL failing, but of the contents of the table changing meaningfully. It's super easy to set up good alerts that detect all kinds of undesired changes or issues in the data. The UI is very intuitive and clear. The reporting/analysis tools are excellent. The triage system is simple but effective.

Anomalo has helped Faire's data organization maintain high-quality data models and pipelines that are key to effective operation. Anomalo diagnoses data quality issues efficiently, providing well-designed automatic alerts integrated into Slack with data visualizations that highlight critical trends and potential errors that require attention. Catching errors that may have otherwise gone unnoticed for days if not weeks has been a major benefit of setting up alerts on tables in our data warehouse. Our cross-functional analytics, product, and engineering partners appreciate and engage with Anomalo's intuitive alerts, which have sparked discussions that have led to better outcomes and resolutions for the data team, our customers, and the larger business.