Handle Missing Values

Gaps in your data can throw off analysis. Missing values are best fixed in the source application by, for example, making it a required field. However, if you can’t do that, you can use CRM Analytics to fill in missing data.

If your data has columns with missing values:

• Use a column profile in a recipe to determine if a column contains missing values and, if so, how many.
• Add the Predict Missing Values transformation to a recipe to fill in missing dimension column values.
• If possible, set a default value for null measures.
• Enable Null Measure Handling to properly handle null numeric values in source data.