Case Study: Nationwide automates enterprise data quality at scale with Anomalo

Nationwide finds more than 3,000 data quality issues with Anomalo

Nationwide, a major insurance and financial services company, faced a significant challenge in maintaining data quality across its vast enterprise data estate of over 5,000 production databases. Their process was complex and reactive, relying on thousands of brittle, manually maintained business rules. Issues often went undetected until they negatively impacted critical reports or regulatory submissions. To address this, they turned to Anomalo for its AI-powered data quality monitoring.

By implementing Anomalo's turnkey solution, which uses statistical analysis to automatically detect true deviations in data, Nationwide was able to find more data quality problems than their previous set of 3,000+ rules. The solution integrated seamlessly with their existing Databricks and Alation infrastructure. This allowed them to proactively stop issues at the source, preventing bad reports from being sent to regulators and establishing a new company-wide policy mandating the use of Anomalo for their most important data assets.

Nationwide