What is batch processing? (Advantages and disadvantages)
Updated 18 November 2022
Automated business processes help companies streamline operations and allow them to focus on more sophisticated tasks. Introduced in the 19th century, the batch processing method is still relevant in supporting companies to cover business needs without user interaction. Learning about batch processing can help you determine whether it's suitable for your team. In this article, we discuss what batch processing is, outline its advantages and disadvantages and provide some examples of batch processing.
What is batch processing?
To answer 'What is batch processing?', batch processing occurs when a computer automates and processes transactions or other repetitive tasks in a group. It's a method for running high-volume, automated data jobs without user interaction. Batch processing is mostly used for end-of-cycle processing, such as generating monthly payrolls or bank reports. Companies can perform batch processing on an as-needed basis or at regularly scheduled times. The process allows users to collect and store data and process that data in a batch window.
Advantages of batch processing
There are several benefits of batch processing, including:
Improved data quality
Batch processing allows computing teams to avoid data errors completely as it automates all components of a processing job. This means data scientists and other IT professionals save time removing errors and inconsistencies while cleansing data. When a computer identifies abnormalities, it flags them immediately for companies to solve. Improved data quality allows companies to make more accurate and well-informed decisions.
Better use of existing computer systems
IT professionals usually carry out processing when computer systems are in low demand. This allows for maximum use of the operating system and ensures companies capitalise on existing resources. Companies can also schedule batch processing to run when systems hit a certain bandwidth, allowing them to use existing systems more intelligently.
In contrast to stream processing, batch processing systems work anytime and anywhere. This allows companies to complete tasks outside of standard business hours. Even during down periods, batch processing can take place in the background of an offline setting. Offline features mean that you can complete processes without impacting the organisation's daily routine. Managers can choose when to start batch processes to avoid disrupting daily activities or overwhelming systems.
Batch processing involves completing process jobs only when computing resources are available. This allows companies to prioritise time-sensitive tasks and schedule batch processes for less urgent activities. Job scheduling and resource allocation ensure companies operate more smoothly and efficiently.
Batch processing helps companies cut down on labour, equipment and other operational costs. It reduces the need for human oversight, allowing companies to delegate personnel to more sophisticated duties. This supports greater workplace productivity and provides the company with more revenue to invest in new opportunities and equipment.
Faster business intelligence
This processing method allows companies to process large volumes of data more quickly. Batch processing prepares many records in one single transaction, thereby improving processing time. Faster processing means business intelligence becomes available more quickly, increasing decision-making abilities in time-sensitive scenarios.
Batch processing is a less complex system when compared to other methods, such as stream processing. This is because it doesn't require system support or specialist hardware to input data. Batch processing systems usually require less maintenance and provide a low barrier-to-entry solution for data processing. Process automation means that companies don't have to spend time educating teams on how to perform certain tasks.
Batch processing gives managers and other personnel more time to carry out their own jobs without having to supervise batches. Systems send alerts to appropriate staff members where problems arise, allowing them to otherwise work uninterrupted. There's no pressure to log in or adjust settings before processing begins due to job scheduling capabilities.
Disadvantages of batch processing
Considering the pitfalls associated with batch processing can better help companies determine whether this approach is suitable for their needs. Some disadvantages of batch processing include:
Deployment and training
In-house training is necessary to manage batch processing systems and technologies. Training ensures managers understand what triggers a batch, what exception notifications mean and how to schedule processing and other essential functions. It's also important for managers to set time aside for reading systems manuals and communicating system functions to staff.
Batch processing reduces the accuracy of processing metrics, such as times of export orders, where late visibility of exceptions and issues occur. Providing late visibility introduces risk into the process and can impact operational productivity. Proactive management of systems is necessary to ensure processed batches reflect the real-time processing of importing and exporting events.
Batch processing infrastructure is an expensive investment when paid upfront. Small or start-up businesses may struggle to justify or accommodate the costs of batch processing, making system implementation unfeasible. Batch processing requires an organisation to have enough hardware to sustain the system and data entry staff to monitor and interpret data. This means that batch processing may be most beneficial to guarantee reduced costs for large businesses that process bulky data on a continuous basis.
Debugging is the process of identifying and removing errors from computer software and hardware. Batch processing systems are complex, requiring IT professionals who are familiar with the programme to operate and troubleshoot them. This may mean that companies spend more money hiring an information technology specialist or training existing staff members.
Examples of batch processing
Learning some examples of batch processing allows you to determine the best use cases and how this method can feature in everyday business operations. Some examples of batch processing include:
After-hours batch processing is common in the banking industry where companies use it to process transactions, such as international money transfers. Conducting these processes beyond standard business hours allows banking staff to focus their days around assisting branch clients and enhancing the client experience. Other bank transactions companies may carry out with batch processing include bank statements and financial reports.
Batch processing is useful in the manufacturing industry when producing line-item invoices for organisations that accrue data and produce one main product or output at a certain time. This helps manufacturing teams keep track of their resources and production costs, while also facilitating good relationships with suppliers. Batch processing also helps with supply chain and fulfilment.
Manufacturers can use batch processing to produce operational reports for production lines. Businesses may produce operational reports in a batch window and deliver them to managers immediately. These reports help managers stay up to date with day-to-day operations and include information on resource expenditures, production costs, process examinations and accounting details. Operational reports produced through batch processing help management make more informed decisions for project completion.
Companies can use batch processing to process data records and calculate accurate charges. For instance, a telecommunications company may run a monthly batch job to process all call data and determine customer phone charges. The system bases bills on phone call information and run times.
Alternatives to batch processing
Learning about alternative systems can help you evaluate which method is most suitable for the business. Here are three alternative systems companies can use instead of batch processing:
Stream processing is a method that involves processing a series of data as soon as it's received or created. Stream processing allows companies to perform multiple tasks on incoming data serially or parallel to one another. These tasks generate a stream processing pipeline, which involves the generation of the stream data, the processing of the data and delivery of the data to its necessary end location.
Stream processing is applicable when a company produces a continuous stream in a constant and instant flow rather than exporting a large amount of data at one time. Stream processing helps carry out a number of transactions frequently and quickly. Some examples of when to use stream processing include real-time fraud and anomaly detection, AI analytics, share prices and personalised marketing and advertising.
Real-time operating systems
A real-time operating system (RTOS) processes data as it arrives, with no buffers or delays. These systems are useful when its necessary to perform tasks within a tight time boundary or according to a specific schedule. There are two types of real-time operating systems, soft real-time and hard real-time systems. The former operates within a few hundred milliseconds, producing results at the scale of human interaction. Hard real-time systems respond within tens of milliseconds or less.
Real-time operating systems are primarily used for systems where failure can result in catastrophic consequences. Some use cases include air traffic control, robotics, emergency braking systems, extra-terrestrial rovers and drones, engine warning systems and engine turbines.
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