derives missing |
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corrects the error present in the data, and derives missing values. |
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Data Cleaning |
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Data Cleaning: This process identifies any duplicate entries, |
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Normalization |
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Normalization: All data must be in one standard unit of measurement and date and currency format. |
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cleaning of the data |
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cleaning of the data are necessary in order to include data coming from various origins: |
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Raw data |
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Raw data may include formats that are not compatible or inconsistent. Hence, transformation and |
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key consideration |
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compatibility of a solution with the source of the data is a key consideration. |
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