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What is data processing?
Data processing is the process of converting raw data into meaningful information. Data conversion to reach the final result, obtaining information, goes through different steps. In other words, it can be considered information processing.
Data is manipulated to produce results that lead to a resolution of a problem or improvement of an existing situation. Similar to a production process, it follows a cycle where the input (raw data) is fed to a process (computer systems) to produce output (information).
Generally, organizations employ computer systems to carry out a series of operations on the data to present, interpret, or obtain information. The process includes activities like data entry, summary, calculation, storage, etc. A useful and informative output is presented in various appropriate forms such as diagrams, reports, graphics, etc.
The stages of the data processing cycle
Collection
Preparation
Input
Processing
Output and interpretation
Storage
Methods of the data processing done electronically
Batch Processing
Batch Processing is a method where the information to be organized is sorted into groups to allow for efficient and sequential processing. Online Processing is a method that utilizes Internet connections and equipment directly attached to a computer. It is used mainly for information recording and research.
Real-Time Processing is a technique that can respond almost immediately to various signals to acquire and process information. Distributed Processing is commonly utilized by remote workstations connected to one big central workstation or server. ATMs are good examples of this data processing method.
Online Processing
This is a method that utilizes Internet connections and equipment directly attached to a computer. This allows for the data stored in one place and being used at an altogether different place. Cloud computing can be considered as an example that uses this type of processing. It is used mainly for information recording and research.
Real-Time Processing
This technique can respond almost immediately to various signals to acquire and process information. These involve high maintenance and upfront cost attributed to very advanced technology and computing power. Time saved is maximum in this case as the output is seen in real-time. For example in banking transactions
Distributed Processing
This method is commonly utilized by remote workstations connected to one big central workstation or server. ATMs are good examples of this data processing method. All the end machines run on a fixed software located at a particular place and make use of exactly the same information and sets of instructions.
Benefits of outsourcing data processing
It will enhance business efficiency
All information obtained through different data sources has to be converted into a variety of suitable formats that can then be utilized by companies. The process of data processing consists of several steps, which need to be handled with precision and skill.
An experienced offshoring service provider can execute this task in an efficient way with careful controls in place, at each step. Regardless of the source, they would be able to convert it into a customized and readable business-friendly format, tailored specifically for your organization’s requirements.
You can focus on the core business goals
Carrying out in-house data processing requires a substantial investment of funds, resources, staff, and equipment, and this investment is bound to increase as the amount of data generated goes up. In addition, it will be a loss to the organization, if, at any time, there is a need for scaling down. A far more cost-friendly approach is to trust the process to an expert who can scale up or down as per your requirements without any hassles.
As they have dedicated and competent data processing services, they will attend to this task while you can focus on the overwhelming competitive market. Outsourcing this non-core task to an expert data processing service provider would help businesses to do what they are actually supposed to do: make critical decisions and take the necessary actions that cause a business’ growth and contributes to revenues.
Data is organized and stored safely
High-quality data processing services ensure that your data gets organized and stored in a safe way. This reduces data loss as well as ensures that data is accessible for data analysis. Without proper data processing, unstructured data can be easily lost in the depths of storage databases.
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