In three articles we are exploring data preparation using Toad Data Point. In the first article we created a data source as a MySQL database table. The data we stored had some shortcomings such as extra spaces, null values, blank values, wrong data types, and duplicate values. We profiled the data to find the issues with the data. In the second article we extracted the data to Toad Data Point. We started to transform the raw data by running auto transform, which trims the extra spaces and performs data type conversions. In this third article we shall remove duplicate data, find and replace missing data, and find and replace blank values, among other transformations.
This is a companion discussion topic for the original entry at https://blog.toadworld.com/data-preparation-using-toad-data-point-3