What's the deal with ML pipelines? Why are they so hyped?

Newbie here. I have seen the term 'pipeline' used invariably in a data scientist's job description on portals. I am trying to understand what that entails. If I wrote a script that takes input a raw dataset and outputs cleaned and transformed dataset, should I write it as "created a preprocessing pipeline" or sth like that on the resume? For instance I do that in every project just to make things more organized in an OOP fashion and get benefits …

datascience deal ml ml pipelines pipelines