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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 analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Invalid or incorrect data needed correction and resubmission with consequences for data and account reconciliation. Data storage was strictly serial on paper tape, and then later to magnetic tape: the use of data storage within readily accessible memory was not cost-effective until hard disk drives were first invented and began shipping in 1957.
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
In the future, tools based on semantic web languages such as RDF, the Web Ontology Language (OWL) and standardized metadata registry will make data mapping a more automatic process. This process will be accelerated if each application performed metadata publishing. Full automated data mapping is a very difficult problem (see semantic translation).
The following is provided as an overview of and topical guide to databases: Database – organized collection of data, today typically in digital form. The data are typically organized to model relevant aspects of reality (for example, the availability of rooms in hotels), in a way that supports processes requiring this information (for example, finding a hotel with vacancies).
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.
A staging area, or landing zone, is an intermediate storage area used for data processing during the extract, transform and load (ETL) process. The data staging area sits between the data source(s) and the data target(s), which are often data warehouses, data marts, or other data repositories. [1] Data staging areas are often transient in ...