Commercially supported by Union.ai, Flyte is a Kubernetes-friendly DAG-based data pipelining framework that can type check material that has been ingested as Data Frames in the Python Pandas format. And Pandera builds on this framework by also providing additional statistical and validations checks against data, allowing an organization build out a data schema that embeds some domain knowledge around the acceptable data ranges and types.
When used together these programs can validate data as correct, throwing out alerts at runtime when they are validated. In machine learning, type safety is vitally important if for no other reason than it can save considerable time and resources.
When used together these programs can validate data as correct, throwing out alerts at runtime when they are validated. In machine learning, type safety is vitally important if for no other reason than it can save considerable time and resources.
