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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 ]
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 ).
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 ...
Both free and paid versions are available. It can handle Microsoft Excel .xls and .xlsx files, and also produce other file formats such as .et, .txt, .csv, .pdf, and .dbf. It supports multiple tabs, VBA macro and PDF converting. [10] Lotus SmartSuite Lotus 123 – for MS Windows. In its MS-DOS (character cell) version, widely considered to be ...
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Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...