Batch processing is a computing approach in which a collection of data or tasks is gathered and processed together rather than handled individually as they arrive. Jobs are typically scheduled to run at defined times or when a required volume of data has been accumulated, making the approach well suited to workloads where immediate results are not essential. It can efficiently handle large volumes of repetitive operations with minimal manual intervention.
Batch processing is commonly used for payroll, billing, transaction reconciliation, data warehouse updates, report generation, and large-scale data transformation. In an industrial setting, for example, sensor records collected throughout a production shift can be processed together to calculate performance metrics, identify recurring issues, or update historical records. Unlike real-time processing, batch processing prioritizes efficient handling of accumulated workloads over immediate response.
