Data processing is the process of gathering and manipulating raw data to produce useful information. In other words, data processing converts unusable data into a valuable form. It involves data organization, modification, storage and final presentation of the wanted information. Processed data is often in form of tables, diagrams, and reports. Processed data in computing comes in form of numeric forms, text, diagrammatic, graphic, video, and audio. Data processing includes processes such as:
Types of data processing
Types of data processing are understood on the basis of technology adopted. Normally, there are three types of data processing: Manual, mechanical and electronic
In this type of data processing, data is processed manually and no electronic or machine is used. The type is less reliable, slow and chances of errors are high. Depending on the data that need to be processed, this type of data processing is also expensive and needs large manpower.
Here data processing is carried out by use of a mechanical device or simple electronic devices such as type writers and calculator. Compared to manual data processing, this type is more reliable and saves time. However, the output is still limited.
This is the best and fastest available type with highest accuracy and reliability. This type requires minimal manpower because it uses a computer. This is the best existing type of data processing because the user can process a very large amount of data within second or minutes.
Data Processing Methods
Data processing methods refer to techniques used to sort or process different types of data. Generally, there are five methods of data processing: batch processing, online Processing, time sharing, multiprocessing and real-time processing.
The main characteristic of this method of data processing is that different jobs of diverse users are processed in the order they are received. The method involves processing of a large amount of data, thus reducing the cost of processing. Examples include payroll, examination, and billing system.
This method is used to carry out real-time processing. The results are shown instantly. The method requires use of internet connection and all data is kept online. Example includes tickets booking for flights, banking systems, and movie tickets.
Also known as an automatic process method, this method ensures that the task received by the system is processed when received. This is sometimes considered as real-time processing.
Multi-processing type uses CPUs to process data. The tasks are divided between various CPUs simultaneously thus increasing efficiency. Task that needs to be done is sent to various CPUs operating parallel within the mainframe. Examples include data processing using mobile, laptops and computers.
Here one CPU is used by many users. All users share one CPU but time allocated to users might differ. As per allocated time, the processing takes place at various intervals for various users.
Benefit of Data Processing to Fintech Companies
Data processing is essential to fintech businesses. With data processing, your fintech business can face the challenges and competition in the industry because it will allow you to focus on the productive activities that your firm should do.
Typically, data processing services including check processing, form processing, image processing and insurance claims processing. Although these may appear minor to your fintech business, they can offer you high impact in the market. Image processing can significantly affect the marketing of your firm. Creating high quality images and putting them in brochures and catalogs will attract your target customers and clients.
Form processing enables you to access all the needed information easier and faster because the forms are available in a way that is easy to understand. These forms include invoices, tax forms, legal forms, email, different kinds of survey and resumes.
While planning a fintech startup, data analysis and processing should be one of the priorities in your plan because proper data processing helps the efficiency of your fintech company, helps you save more energy, money and time.
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