To be clear: the data doesn’t become code.

Data will still fill the roles data, and the goals of cleansing, securing, and documenting it still exist. The data will still be displayed in charts and graphs and tables. With Machine Learning, it may also be “compiled” into an executable format by an ML algorithm. In this context, data fills the same role as code.

The point I was trying to make is that applying the same techniques we have developed for managing code to data (starting with version control) will allow us to manage the data in a different (and better) way than we currently do.

Sorry if I gave a serious response when you were posting that as a joke, hard to tell with just the text. ¯\_(ツ)_/¯