Data processing cycle
To understand the data processing cycle you must first understand that data processing is the restructuring or reordering of data by people or machines to increase its utility and add value for a particular purpose. The data processing cycle is a series of steps that are carried out to extract information from raw data.
Steps for data processing
Data processing consists of the following basic steps:
- Entry
- Prosecution
- Exit.
Entry
Input data is conveniently prepared for processing. The form will depend on the processing machine. For example, when electronic computers are used, the input data can be recorded on any of several types of input media, such as magnetic disks, tapes, etc.
Prosecution
The input data is modified to produce data in a more useful form. For example, paychecks can be calculated from time cards, or a summary of the month’s sales can be calculated from sales orders.
Departure
In this stage, the result of the current processing step is collected. The particular form of the output data depends on the use of the data. For example, the output data may be paychecks for employees.
Stages of the data processing cycle
As discussed above, data processing has three broad stages that have sub-stages or steps involved. These are the steps/processes required between these three general stages. They deal with the collection of data, the choice of processing methods, the practice of data management best practices, the information processing cycle, and the use of the processed data for the intended purpose.
What are the stages of the data processing cycle?
Harvest
The first step in the cycle is to collect the data which is very important because the quality of the data collected will ultimately affect the overall production. The data collected must ensure that it is accurate and meaningful. This step provides the baseline for improving what has been targeted.
Preparation
It is basically the exploitation of the data in a suitable form for its subsequent analysis and processing. The raw data cannot be used directly, instead it must be verified and verified. Preparation is about building all the new data sets from all the data sources that need to be used for further processing. Low data quality can produce misleading results.
Entry
This step is defined as the task of encoding and converting the verified data into a machine-readable format so that it can be processed through software or an application. The data entry process is time consuming and therefore speed and accuracy are a must.
Prosecution
It is the stage where the data is subjected to multiple means and methods of technical exploitations using artificial intelligence algorithms to generate insight from the data. The process can be composed of multiple execution connections that execute instructions relatively, depending on the type of data.
Departure
It is also said as rendering, which is the step where the refined information is conveyed and displayed to the user finally. The output is presented to users in various report forms, such as audio, video, graph, or document viewers.
