Datasets often have missing values due to file corruption, failure to record data points, or other causes. Handling missing data values correctly is critical to developing accurate predictive models. Knowledge Studio makes it easy to identify datasets containing missing values and generate new substitute values based on a variety of substitution algorithms. This video walks you through a simple example of how the software's Substitute Missing Values node works.