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- W4375952803 abstract "The initial step for a data scientist when addressing a business question is to identify the data type, as not all types can be employed in data mining analyses. Accordingly, the data scientist must select a suitable data type that corresponds to the data mining technique and classify the data into categorical and continuous types, regardless of the source of the data. Quality control is a significant factor for the data scientist, particularly if data collection was poorly administered or designed, leading to issues like missing values. Once the data scientist has acquired a relevant dataset, they should inspect the outliers associated with each feature to make sure the data is suitable for analysis. Observing outliers through data visualizations, such as scatter plots, is a common practice among data scientists, highlighting the crucial role of data type determination." @default.
- W4375952803 created "2023-05-10" @default.
- W4375952803 date "2023-06-02" @default.
- W4375952803 modified "2023-10-17" @default.
- W4375952803 title "Data" @default.
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- W4375952803 doi "https://doi.org/10.4018/978-1-6684-4730-7.ch002" @default.
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