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Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.
Forms processing is a process by which one can capture information entered into data fields and convert it into an electronic format. This can be done manually or automatically, but the general process is that hard copy data is filled out by humans and then "captured" from their respective fields and entered into a database or other electronic format.
Electronic data processing (EDP) or business information processing can refer to the use of automated methods to process commercial data. Typically, this uses relatively simple, repetitive activities to process large volumes of similar information.
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.
Data preprocessing can refer to manipulation, filtration or augmentation of data before it is analyzed, [1] and is often an important step in the data mining process. Data collection methods are often loosely controlled, resulting in out-of-range values, impossible data combinations, and missing values , amongst other issues.
Data processing modes or computing modes are classifications of different types of computer processing. [1] Interactive computing or Interactive processing, historically introduced as Time-sharing; Transaction processing; Batch processing; Real-time processing
In information theory, data compression, source coding, [1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation. [2] Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in ...
Data preparation is the act of manipulating (or pre-processing) raw data (which may come from disparate data sources) into a form that can be readily and accurately analysed, e.g. for business purposes.