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Data preparation using Toad Data Point - 1


Data as it is collected (raw data) is often not in a state suitable for an end user. Data preparation, a term used in data science, refers to the task of preparing data so that it can be reliably used or saved for later use. Raw data may include erroneous data, duplicate data, missing data in the form of null values or blank values, extra spaces, wrong data types, and unsorted data; to list some of the shortcomings possible. Toad Data Point provides several features for data preparation.

This is a companion discussion topic for the original entry at