Our methodology is based on the standard Cross Industry Standard Process for Data Mining (CRISP-DM) defined by Teradata, among others, in 1997. It continues being the standard methodology used by the Data Science community.
In this methodology, Data Scientists work to understand business and data for modeling process, making multiple iterations of the models (by training and evaluating multiple model experiments) until the right model is found.
It’s important to understand that Data Scientists start using ModelOps once a good model is found and ready to operationalize. We don’t cover the data ingestions, preparation, or model experimentation stages. We let the user to use their own tools and environments in combination with Vantage for that.