Given the growing amount of weighty decisions that are derived from large data sets, either directly or as training input for machine learning models, it's important to understand the gaps, flaws and potential biases in your data. Google's Facets project provides two helpful tools in this space: Facets Overview and Facets Dive. Facets Overview visualizes the distribution of values for features in a data set, can show training and validation set skew and can be used to compare multiple data sets; Facets Dive is for drilling down and visualizing individual data points in large data sets, using different visual dimensions to explore the relationships between attributes. They're both useful tools in carrying out ethical bias testing.