Electronic Data Processing System

Electronic Data Processing System

Today's information technology has significantly changed the way industries process information. Electronic data processing (EDP) has had a considerable impact on exchanging computer-generated information. However, the data collected by organizations usually varies and may include unstructured and structured data. EDP allows you to manage an organization's data sets efficiently.

Data Processing

As the name suggests, data processing is collecting and converting raw information to a meaningful format. On the other hand, data processing systems refer to the devices, procedures, and resources used to store data and convert it into outputs. The data collection process follows several steps, including:

  • Collection and validation
  • Preparation and sorting
  • Inputs
  • Processing
  • Analytics
  • Reporting

Data processing methods include:

  • Manual
  • Automatic
  • Electronic

Many organizations consider electronic data processing extremely useful in processing information. Some of the benefits of EDP are simplicity and adaptability.

Significance of Data Processing Method

The data processing method you choose determines your response time and output reliability. Therefore, you need to choose your data processing method carefully. It is also essential to understand the distinction between data processing and data processing systems. The former refers to the rules that convert raw data into information. On the other hand, EDP refers to the applications that perform data processing.

Types of Data Processing

Transaction Processing

This type of data processing is typically deployed in mission-critical operations. It is ideal for business operations that have such a significant impact on the organization. The failure of transaction processing can adversely affect an organization's operations. One of the most critical factors in transaction processing is availability. The availability of transaction processing can be influenced by various factors, including hardware and software.

The hardware of transaction processing systems should be redundant; it is designed to allow partial but not complete failures. When the system experiences partial failure, redundant parts of the hardware can keep it running.

On the other hand, transaction processing system software should be designed for quick recovery from failure. This is typically achieved through transaction abstraction, which means software failure causes uncommitted transactions to abort, allowing the system to reboot quickly.

Distributed Processing

In some cases, huge data sets may not fit on one machine. A distributed processing system's primary function is to break down large data sets and store them across multiple computers or servers. This means that data sets can be reallocated to available servers if one of the servers fails. An excellent distributed processing system should have high fault tolerance.

One of the benefits of distributed processing systems is they save on costs. Distributed processing systems eliminate the need for businesses to invest in multiple mainframe computers and the machines' maintenance. Examples of distributed processing systems include stream and batch processing.

Other data processing types include real-time, batch, and multi-processing systems. It is essential to prepare data before it can be processed and analyzed. Data processing systems simplify the process of data preparation for analysis.

Electronic data processing systems have many advantages. They provide real time access to data on internal networks and the Internet. In addition, electronic data processing saves on labor costs.

 

Electronic Data Processing System