Data processing is the collection and manipulation of data in the usable and desired way. There are three main methods of data processing: manual, mechanical and electronic. Manual data processing is time consuming and error-prone, while mechanical data processing processes data through mechanical devices such as typewriters, mechanical printers, and other devices. Electronic data processing (EDP) is the most advanced method, where the computer processes data automatically and seamlessly with predefined instructions from data specialists.
Batch data processing is a technique in which the data to be processed or the programs to be executed are collected in groups to allow convenient and efficient serial processing. Online data processing is often confused with real-time data processing; they both receive and process data simultaneously, but with online processing, the user can extract data anytime, anywhere. Data processing starts with raw data and converts it into a more readable format (graphics, documents, etc.). Collecting data is the first step in data processing.
Data preparation is the stage in which raw data is cleaned and organized for the next stage of data processing. Data entry is the first stage in which raw data begins to take the form of usable information. The final stage of data processing is storage. The future of data processing is in the cloud, offering faster, higher-quality data for every organization to use and more valuable information to extract.
Big data is changing the way we all do business and staying agile and competitive depends on having a clear and effective data processing strategy.