In what situation is Batch Processing typically preferred over real-time processing?

Batch processing is typically preferred over real-time processing in situations where data can be accumulated without pressing time constraints. This method allows for the collection of a large amount of data over a specified period, which is then processed all at once. This is particularly useful for scenarios that do not demand immediate results or for operations that can tolerate some delay in processing.

For example, payroll processing is often conducted in batches because employee data can be collected throughout the pay period and processed together, minimizing the need for constant monitoring and immediate feedback. It optimizes resource use, ensuring that system processes are not bogged down by isolated transactions that could otherwise be handled together, leading to more efficient operation and reduced costs.

In contrast, immediate transaction feedback or unique processing needs would necessitate real-time processing, where transactions are dealt with individually and immediately. Furthermore, high transaction volumes are typically managed in more sophisticated ways, where batch processing would allow for effective handling of a very large set of data more comfortably than real-time systems. Hence, the most suitable scenario for batch processing is one where there are no urgent time constraints, making the selection of option B accurate.