Computer data processing is any process that uses a computer program to enter data and summarise, analyse or otherwise convert data into usable information. It involves recording, analysing, sorting, summarising, calculating, disseminating and storing data. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems. Nevertheless, the terms are roughly synonymous, performing similar conversions; data-processing systems typically manipulate raw data into information, and likewise information systems typically take raw data as input to produce information as output.
Data processing may or may not be distinguished from data conversion, when the process is merely to convert data to another format, and does not involve any data manipulation.
Scientific data processing usually involves a great deal of computation (arithmetic and comparison operations) upon a relatively small amount of input data, resulting in a small volume of output. In the early days of computers, the emphasis was upon scientific data processing. This refers to a class of programs that organize and manipulate data, usually large amounts of numeric data. Accounting programs are the prototypical examples of data processing applications. In contrast, word processors, which manipulate text rather than numbers, are not usually referred to as data processing applications. A processing device is (As part of a computer) a monitor (the screen).
Commercial data processing involves a large volume of input data, relatively few computational operations, and a large volume of output (see Information systems).
When the domain from which data are harvested is a science or engineering field, the terms data processing and information systems are considered too broad, and the more specialized term data analysis is typically used. Data analysis, arguably a special kind of data processing, focusses on highly-specialized and highly-accurate algorithmic derivations and statistical calculations that are less often observed in the typical general business environment.
A divergence of culture between data processing in general and data analysis is exhibited in the numerical representations generally used; In data processing, measurements are typically stored as integers, fixed-point or binary-coded decimal representations of numbers, whereas the majority of measurements in data analysis are stored as floating-point representations of rational numbers.
For data analysis, packages like DAP, gretl or PSPP are often used.
Basically, data are nothing but facts (organized or unorganized) which can be converted into other forms to make it useful, clear and practically used. This process of converting facts to information is Processing. Practically all naturally occurring processes can be viewed as examples of data processing systems where "observable" information in the form of pressure, light, etc. are converted by human observers into electrical signals in the nervous system as the senses we recognize as touch, sound, and vision. Even the interaction of non-living systems may be viewed in this way as rudimentary information processing systems. Conventional usage of the terms data processing and information systems restricts their use to refer to the algorithmic derivations, logical deductions, and statistical calculations that recur perennially in general business environments, rather than in the more expansive sense of all conversions of real-world measurements into real-world information in, say, an organic biological system or even a scientific or engineering system.
In order to be processed by a computer, data needs first be converted into a machine readable format. Once data are in digital format, various procedures can be applied on the data to get useful information. Data processing may involve various processes, including:
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