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Summary

• Data attribute types: nominal, binary, ordinal, interval-scaled, ratio-scaled
• Many types of data sets, e.g., numerical, text, graph, Web, image.
• Gain insight into the data by:
• Basic statistical data description: central tendency, dispersion, graphical displays
• Data visualization: map data onto graphical primitives
• Measure data similarity
• Above steps are the beginning of data preprocessing.
• Many methods have been developed but still an active area of research.