When data is first read into Modeler, it is important to check the data to make sure it was read correctly. Typically, using a Table node can help you get a sense of the data and inform you of some potential issues that you may have. However, the Data Audit node is a better alternative to using a Table node, as it provides a more thorough look at the data.
Before modeling takes place, it is important to see how records are distributed within the fields in the dataset. Knowing this information can identify values that, on the surface, appear to be valid, but when compared to the rest of the data are either out of range or inappropriate. Let's begin by opening a stream that has the modifications we made in the previous ...
