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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]
Isolation is typically enforced at the database level. However, various client-side systems can also be used. It can be controlled in application frameworks or runtime containers such as J2EE Entity Beans [2] On older systems, it may be implemented systemically (by the application developers), for example through the use of temporary tables.
For example, in address book software, the basic storage unit is an individual contact entry. As a bare minimum, the software must allow the user to: [6] Create, or add new entries; Read, retrieve, search, or view existing entries; Update, or edit existing entries; Delete, deactivate, or remove existing entries
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An example of a chart containing gratuitous chartjunk. This chart uses a large area and much "ink" (many symbols and lines) to show only five hard-to-read numbers, 1, 2, 4, 8, and 16. Chartjunk consists of all visual elements in charts and graphs that are not necessary to comprehend the information represented on the graph, or that distract the ...
2015/10/23 Origin 2016. First version to support Apps in Origin, also added R support. 2014/10 Origin 2015 [6] added graph thumbnail previews, project search, heat map, 2D kernel density plot and Python support. 2013/10 Origin 9.1 [7] SR0 added support for Piper diagram, Ternary surface plot etc.
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