This document discusses how missing data can provide valuable insights and opportunities for improvement. It notes that missing data can reveal underlying relationships, patterns, and reasons for missing values. The document recommends identifying the underlying causes of missing data, considering how it was collected, and exploring options for handling it like imputation or indicator variables. It also emphasizes that missing data flags opportunities to enhance the data collection process and pipeline. The overarching message is that missing data, when properly analyzed, can be used to fix issues and improve the value of a data set.