Data Processing: Batch or Real Time? The Need of Data Processing in Business
The carrying out of various operations on raw data from software to retrieve, transform, or classify information is what you call “data processing”.
Mostly, this happens on software programs where a set of inputs produces a defined set of outputs, as manual processing is becoming more and more obsolete and inefficient.
There are two common types of data processing, namely Batch Processing and Real-Time Processing. The determination on whether to use one over the other will depend on the following:
- The type and volume of data
- The time that the data needs to be processed and
- Which process suits a certain business.
The two types help businesses handle information seamlessly. However, like most things, both have advantages and disadvantages.
Batch Data Processing
This is an efficient way of processing high/large volumes of data where a group of transactions is collected over a certain period of time. In the batch method, there is collecting, entering, processing of information and the production of the batch outputs. This method requires separate programs for input, process, and output. Examples of software programs that use this kind of data processing are payroll and billing systems.
- Ideal for processing large volumes of data/transaction for it increases efficiency rather than processing each individually.
- Can be done or processed independently during less-busy times or at a desired designated time.
- It offers cost efficiency for the organization by carrying out the process (data reconciliation for the master file) when needed.
- It allows a good audit trail.
- The very disadvantage of batch systems or processing is the time delay between the collection of data (transaction receiving) and getting the result (output in the master file) right after.
- The Master File (The organization’s big data) is not always kept up to date.
- One time process can be very slow.
Real-Time Data Processing
In contrast with batch, real-time data processing involves continuous input and output of data. Thus, it is in a short period of time. Few examples of programs that use such methods are bank ATMs, customer services, radar systems, and Point of Sale (POS) Systems. POS uses this data processing method to update the inventory, provide inventory history, and sales of a particular item – allowing business to handle payments in real time.
With this kind of data method, every transaction is directly reflected to the master file so that it is always updated.
- No significant delay in response.
- Information is always up to date thus giving the organization the ability to take immediate action when responding to an event, issue or scenario in the shortest possible span of time.
- It could also give the organization the ability to gain insights from the updated data to detect patterns for possible identification of either opportunities or threats to the organization’s business.
- This type of processing is more expensive and complex.
- Real-time processing is a bit tedious and more difficult for auditing.
- Need for implementation of daily data backups (depends on transaction frequency) and the necessity to ensure the retention of the most recent data transaction.
The decision to select the best data processing system will greatly depend on the current system in your business. So, choose the one that best suit your business system.
Have you tried using one of these methods? How will you compare the two methods?