To add on to the exceptions section at the end, in data engineering you generally need to denormalize/flatten/materialize (or whatever term your org uses) data

To add on to the exceptions section at the end, in data engineering you generally need to denormalize/flatten/materialize (or whatever term your org uses) data and tables downstream of your gold source. While you can apply some principles from the article in DE many devs make the mistake of doing it fully and use views which usually end up far less performant than a standard scheduled create/replace statement would produce.