Data processing is any computer process that converts data into information or knowledge. The processing is usually assumed to be automated and running on a computer. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems to emphasize their practicality. Nevertheless, both 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, data
are defined as numbers
that represent measurements
from observable phenomena. A single datum
is a single measurement from observable phenomena. Measured information is then algorithmically derived and/or logically deduced and/or statistically calculated from multiple data. (evidence
is defined as either a meaningful answer to a query
or a meaningful stimulus that can cascade into further queries.
For example gathering seismic data leads to alteration of seismic data to suppress noise, enhance signal and migrate seismic events to the appropriate location in space. Processing steps typically include analysis of velocities and frequencies, static corrections, deconvolution, normal moveout, dip moveout, stacking, and migration, which can be performed before or after stacking. Seismic processing facilitates better interpretation because subsurface structures and reflection geometries are more apparent.
More generally, the term data processing
can apply to any process that converts data from one format to another, although data conversion
would be the more logical and correct term. From this perspective, data processing becomes the process of converting information
and also the converting of data back into information. The distinction is that conversion doesn't require a question (query) to be answered. For example, information
in the form of a string of characters forming a sentence in English is converted or encoded
meaningless hardware-oriented data to evermore-meaningful information as the processing proceeds toward the human being.
Conversely, that simple example for pedagogical purposes here is usually described as an embedded system
(for the software resident in the keyboard itself) or as (operating-)systems programming
, because the information is derived from a hardware interface and may involve overt control of the hardware through that interface by an operating system. Typically control of hardware by a device driver manipulating ASIC
registers is not viewed as part of data processing proper or information systems proper, but rather as the domain of embedded systems or (operating-)systems programming
. Instead, perhaps a more conventional example of the established practice of using the term data processing
is that a business has collected numerous data concerning an aspect of its operations and that this multitude of data must be presented in meaningful, easy-to-access presentations for the managers who must then use that information to increase revenue or to decrease cost. That conversion and presentation of data as information is typically performed by a data-processing application
When the domain from which the data are harvested is a science or an engineering, data processing and information systems are considered too broad of terms and the more specialized term data analysis
is typically used, focusing on the highly-specialized and highly-accurate algorithmic derivations and statistical calculations that are less often observed in the typical general business environment. In these contexts data analysis packages like DAP
are often used. This divergence of culture is exhibited in the typical numerical representations used in data processing versus numerical; data processing's measurements are typically represented by integers
or by fixed-point
or binary-coded decimal
representations of numbers whereas the majority of data analysis's measurements are often represented by floating-point
representation of rational numbers.
Practically all naturally occurring processes can be viewed as examples of data processing systems
where "observable" information in the form of pressure
, etc. are converted by human observers
signals in the nervous system
as the senses
we recognize as touch
, 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 system
s 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.
Elements of Data Processing
In order to be processed by a computer, the data needs first to be converted into a machine readable format. Once data is in digital format, various procedures can be applied on the data to get useful information. Data Processing includes all the processes from Data Entry
up to Data Mining
- Linda B., Bourque, Linda B., Bourgue, Virginia A., Clark, Processing Data: The Survey Example (Quantitative Applications in the Social Sciences), Sage Publications, Inc. (December 14, 2006), ISBN 0803947410
- Definitions of Data Processing on Google