With the rise of CD4ML, operational aspects of data engineering and data science have received more attention. Automated data governance is one aspect of this development. Great Expectations is a framework that enables you to craft built-in controls that flag anomalies or quality issues in data pipelines. Just as unit tests run in a build pipeline, Great Expectations makes assertions during execution of a data pipeline. This is useful not only for implementing a sort of Andon for data pipelines but also for ensuring that model-based algorithms remain within the operating range determined by their training data. Automated controls like these can help distribute and democratize data access and custodianship. Great Expectations also ships with a profiler tool to help understand the qualities of a particular data set and to set appropriate limits.