UMAP is a powerful tool for exploratory data analysis, but without a clear understanding of how it works, it can easily lead to confusion and misinterpretation.
Code is a useful representation of a data analysis for the purposes of transparency and opennness. But code alone is often insufficient for evaluating the quality of a data analysis and for determining why certain outputs differ from what was expected. Is there a better way to represent a data analysis that helps to resolve some of these questions?
A data analysis can fail if it doesn't present a coherent story and "close all the doors". Such a failure is not simply a problem with communication, but often indicates a problem with the details of the analysis itself.