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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.
Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1]
In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods.
The data modeling process. The figure illustrates the way data models are developed and used today . A conceptual data model is developed based on the data requirements for the application that is being developed, perhaps in the context of an activity model.
Data analysis; Data classification (business intelligence) Data entry; Data entry clerk; Data onboarding; Data processing (disambiguation) Data processing inequality; Data processing machine; Data processing unit; Data reporting; Data scraping; Data sonification; Data validation; Disaggregated storage; DOME MicroDataCenter; DOME project
Data entry is the process of digitizing data by entering it into a computer system for organization and management purposes. It is a person-based process [ 1 ] and is "one of the important basic" [ 2 ] tasks needed when no machine-readable version of the information is readily available for planned computer-based analysis or processing.
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