CandleFocus Glossary Editor
Batch processing is a computing technique used to automate and quickly process multiple transactions as a single, large batch. It is one of the most conventional methods of data processing, commonly found in accounting, payroll, and other business-related operations. Specifically, it is a form of data processing when multiple transactions are collected as input and processed as a single, large volume of data, rather than individually processing multiple, smaller chunks of data.
The use of batch processing has been around for a long time, with systems that were hardwired to input related data and store it for processing later. In modern systems, batch processing is used to help manage everyday tasks such as payroll, end-of-month reconciliation, or settling trades overnight. In these cases, all of the data is collected and grouped into a "batch" for processing to take place at a later time.
One of the key advantages to batch processing is the cost savings, especially over time. When implemented properly, batch processing can reduce human labor and manual data entry. The cost of building such a system can be initially expensive, but over time, the cost savings and efficiencies will far outweigh the initial investment.
An additional benefit to batch processing is efficiency within the organization. By automating the transactions, organizations can save time and resources. In addition, batch processing can also be used to detect and eliminate any errors more quickly and efficiently.
As technology has advanced over the years, so too has batch processing. Modern batch processing solutions are now more interconnected, allowing for the automation of the output from one step in the process to the input of the next. This results in faster, more efficient processes and an overall smoother handling of data-intensive tasks.
In summary, batch processing is a conventional data processing technique that provides cost savings and efficiency to organizations. By collecting data and processing it as a single, large volume, organizations can expedite everyday tasks as well as detect and eliminate errors quickly. Although it can initially be a costly upfront investment, the cost savings and efficiencies over time are significant. As such, batch processing remains a popular data processing choice in a wide variety of organizations.
The use of batch processing has been around for a long time, with systems that were hardwired to input related data and store it for processing later. In modern systems, batch processing is used to help manage everyday tasks such as payroll, end-of-month reconciliation, or settling trades overnight. In these cases, all of the data is collected and grouped into a "batch" for processing to take place at a later time.
One of the key advantages to batch processing is the cost savings, especially over time. When implemented properly, batch processing can reduce human labor and manual data entry. The cost of building such a system can be initially expensive, but over time, the cost savings and efficiencies will far outweigh the initial investment.
An additional benefit to batch processing is efficiency within the organization. By automating the transactions, organizations can save time and resources. In addition, batch processing can also be used to detect and eliminate any errors more quickly and efficiently.
As technology has advanced over the years, so too has batch processing. Modern batch processing solutions are now more interconnected, allowing for the automation of the output from one step in the process to the input of the next. This results in faster, more efficient processes and an overall smoother handling of data-intensive tasks.
In summary, batch processing is a conventional data processing technique that provides cost savings and efficiency to organizations. By collecting data and processing it as a single, large volume, organizations can expedite everyday tasks as well as detect and eliminate errors quickly. Although it can initially be a costly upfront investment, the cost savings and efficiencies over time are significant. As such, batch processing remains a popular data processing choice in a wide variety of organizations.