Batch Processing
Batch processing is a computing paradigm where data is collected, grouped into batches, and processed in bulk at scheduled intervals, rather than in real-time. It involves executing a series of jobs or tasks on large datasets without user interaction, often during off-peak hours to optimize resource usage. This approach is commonly used for data analytics, ETL (Extract, Transform, Load) operations, and report generation.
Developers should learn batch processing for handling large-scale data workloads efficiently, such as processing log files, generating daily reports, or performing data transformations in data pipelines. It is essential in scenarios where real-time processing is unnecessary, and cost-effectiveness, reliability, and scalability are priorities, like in financial systems, big data analytics, and batch-oriented applications.