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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 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.
Electronic data interchange (EDI) is the concept of businesses electronically communicating information that was traditionally communicated on paper, such as purchase orders, advance ship notices, and invoices. Technical standards for EDI exist to facilitate parties transacting such instruments without having to make special arrangements.
Information processing may refer to: Data processing in computer science, the collection and manipulation of digital data to produce meaningful information, esp. Electronic data processing, the use of automated methods to process data; Information processing (psychology) an approach to the goal of understanding human thinking
Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. [90] It employs techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer science. data structure
The data can be collected from one or more sources and it can also be output to one or more destinations. ETL processing is typically executed using software applications but it can also be done manually by system operators. ETL software typically automates the entire process and can be run manually or on recurring schedules either as single ...
Data science is a field that uses scientific and computing tools to extract information and insights from data, driven by the increasing volume and availability of data. [46] Data mining , big data , statistics, machine learning and deep learning are all interwoven with data science.
This data processing was accomplished by processing punched cards through various unit record machines in a carefully choreographed progression. [5] This progression, or flow, from machine to machine was often planned and documented with detailed flowcharts that used standardized symbols for documents and the various machine functions. [ 6 ]