DataOps is likened to a grain mill that builds data assets from raw data. MLOps is likened to a bread factory that uses the data assets from DataOps to build machine learning models. DevOps is likened to a restaurant that packages the models from MLOps into applications for end users. Each stage involves building, testing, and releasing products through an automated delivery pipeline with feedback loops for continuous improvement.