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Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data (e.g. sorting) or parsing the data into predefined data structures, and finally depositing the resulting content into a data sink for storage and future use. [1]
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. [note 1]
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.
Raw data (sometimes colloquially called "sources" data or "eggy" data, the latter a reference to the data being "uncooked", that is, "unprocessed", like a raw egg) are the data input to processing. A distinction is made between data and information , to the effect that information is the end product of data processing.
A special form of data-flow plan is a site-oriented data-flow plan. Data-flow diagrams can be regarded as inverted Petri nets, because places in such networks correspond to the semantics of data memories. Analogously, the semantics of transitions from Petri nets and data flows and functions from data-flow diagrams should be considered equivalent.
Often parts of the punched card installation, in particular sorters, were retained to present the card input to the computer in a pre-sort form that reduced the processing time involved in sorting large amounts of data. [9] Data processing facilities became available to smaller organizations in the form of the computer services bureau. These ...
It also is a buzzword [7] and is frequently applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence (e.g., machine learning) and business intelligence.
Chapter 8 – Recursion; Volume 5 – Syntactic algorithms Chapter 9 – Lexical scanning (also includes string search and data compression) Chapter 10 – Parsing techniques; Volume 6 – The Theory of context-free languages. Chapter 11 – Mathematical linguistics; Volume 7 – Compiler techniques Chapter 12 – Programming language translation