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Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [ 1 ]
Data sanitization methods are also applied for the cleaning of sensitive data, such as through heuristic-based methods, machine-learning based methods, and k-source anonymity. [ 2 ] This erasure is necessary as an increasing amount of data is moving to online storage, which poses a privacy risk in the situation that the device is resold to ...
Data erasure (sometimes referred to as data clearing, data wiping, or data destruction) is a software-based method of data sanitization that aims to completely destroy all electronic data residing on a hard disk drive or other digital media by overwriting data onto all sectors of the device in an irreversible process. By overwriting the data on ...
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 ...
Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...
A browser's cache stores temporary website files which allows the site to load faster in future sessions. This data will be recreated every time you visit the webpage, though at times it can become corrupted. Clearing the cache deletes these files and fixes problems like outdated pages, websites freezing, and pages not loading or being ...
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