Anomalo x American Express
Ensure trusted, high-quality data with Anomalo—seamlessly integrated into your American Express infrastructure. Leading financial institutions like Discover use Anomalo to automate data quality monitoring at scale, reducing manual effort and improving analytics accuracy.
With Anomalo, you can proactively monitor high-volume transaction data in many data warehouses, detecting anomalies and preventing issues before they impact fraud models, credit risk assessments, and customer insights.
Our seamless integration with Alation and Databricks ensures effortless deployment, surfacing data health insights directly in your existing workflows. Automate compliance checks, enhance reporting accuracy, and drive operational efficiency with AI-powered anomaly detection.
Strengthen data governance, accelerate decision-making, and achieve enterprise-wide data reliability—only with Anomalo.
Solution
Out-of-the-Box Data Quality at Scale
Detect issues across your most critical datasets without writing any rules. Anomalo’s ML-powered monitoring surfaces anomalies, freshness gaps, schema changes, and more with minimal configuration.
Built for Your Modern Data Stack
Seamlessly integrate with data platforms like Databricks, Snowflake, and Google BigQuery, as well as data catalogs like Atlan and Alation, so you can monitor data quality directly where you already work.
Easy Procurement on Marketplace
Anomalo is available on both Google Cloud Marketplace and Snowflake Marketplace, making it fast and simple for you to purchase, deploy, and apply credits toward committed cloud spend.
Automated Root Cause Analysis
Instantly understand why a data issue occurred with automated root cause insights that help your engineering and data teams fix problems faster.
Designed for the Entire Data Team
Anomalo empowers data stewards, analysts, and engineers with customizable monitors, alerting, and governance workflows, so quality doesn’t rely on a single team.
Financial-Grade Precision
Anomalo helps Fortune 500 financial services leaders catch revenue-impacting issues like missing transactions, reconciliation mismatches, and delayed data feeds—before they impact downstream reports or models.