Batch Processing
Batch processing is a computing paradigm where large volumes of data are collected, processed, and analyzed in groups (batches) at scheduled intervals, rather than in real-time. It involves executing a series of jobs or tasks automatically without manual intervention, often during off-peak hours to optimize resource usage. This approach is commonly used for data transformation, reporting, ETL (Extract, Transform, Load) operations, and bulk data updates.
Developers should learn batch processing for handling large-scale data workloads efficiently, such as generating daily reports, processing log files, or performing data migrations in systems like data warehouses. It is essential in scenarios where real-time processing is unnecessary or impractical, allowing for cost-effective resource utilization and simplified error handling through retry mechanisms. Use cases include financial transaction settlements, payroll processing, and big data analytics pipelines.