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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 editing is defined as the process involving the review and adjustment of collected survey data. [1] Data editing helps define guidelines that will reduce potential bias and ensure consistent estimates leading to a clear analysis of the data set by correct inconsistent data using the methods later in this article. [2]
The problem of database repair is a question about relational databases which has been studied in database theory, and which is a particular kind of data cleansing. The problem asks about how we can "repair" an input relational database in order to make it satisfy integrity constraints.
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 ...
Note: that data-sort-type=VALUE must go in the header cell with the sorting icon. That will be the lowest header cell. That will be the lowest header cell. (See Help:Sortable tables § Forcing a column to have a particular data type ).
Some source data tables only use the codes. Wrap them in brackets {{ABC}} to create full-name country links. To do so click on the wikitext source editing link. Click on "Advanced" in the editing toolbar. Then click on the search and replace icon on the right. Put a check in the box called "Treat search string as a regular expression."