dr-anomalies-report

Anomaly detection for financial data tables is automated by generating a comprehensive report that identifies data quality issues and profiles fields. It uses built-in checks to find anomalies and outputs an Excel deliverable with findings categorized by severity.

Data profiling for financial reporting generates statistics for numeric and categorical fields within your data tables. This process helps you understand the structure and quality of your data before running month-end close checks.

You can generate an Excel report for anomaly detection without manual configuration by running automated checks on any Datarails Finance OS table. It works with or without client profiles and requires no setup to identify data quality issues.

The anomaly detection report adapts to any Datarails Finance OS table automatically. It works seamlessly with or without client profiles, ensuring broad compatibility across your financial reporting environment.

You filter financial data anomalies by configurable severity levels including critical, high, medium, or low. The generated Excel deliverable organizes all identified data quality findings according to these severity categories.