Data quality is one of the essential parts of data processing flows to enable accuracy and reliability for actionable usage data. Maintaining high-quality data is crucial for producing accurate results, preventing revenue losses, and building trust in the data. Data quality issues may occur for many reasons like data source not complete or misconfigured processing logic. It is important to correct the data before it is used to create a single source of truth for billing or any other similar purpose.
Data correction is the feature provided by the Usage Engine Cloud Edition to identify and gain access to corrupt or invalid data.
Data can be validated using a validate function which can be easily configured to check one or multiple fields on the data. The records that fail validation rules while execution are accumulated in the data correction. Using Data Correction UI, users can view, correct, re-process, and delete individual or multiple invalid records.