There’s a two-part process at work in preparing batch jobs. The first is determining the necessary workflows that need to occur and loading the job queue accordingly.

Then the operating system takes over, beginning the data-processing actions that will enable the system to process large volumes of data. The job processing then pushes the high-volume data sets.

Companies can set up batch processes to happen as they need them to occur, but they are usually set up to occur automatically as either a beginning-of-day (BOD) activity or an end-of-day (EOD) activity. If you use a BOD process, it'll implement an end-of-transaction input (EOTI) before that day’s batches run. If the process takes place at the end of the day, it'll generate an end-of-financial input (EOFI) once the batch finishes running.

While batch jobs significantly increase the organization’s computing output, there are certain caveats surrounding the use of batch jobs. Depending on how and in what amount they’re being used, batch jobs can represent a significant strain on a company’s computer system.

For this reason, the running of batches is typically scheduled to coincide with a span of time when the company’s compute resources are less strained. This period is known as the batch window.