It's a common term used in data governance. It's found less in the academic literature, and more in software demos and vendor brochures. You'll also hear "data lineage", which is the context in which the term arises.
"Provenance" just means where the data came from. [1]
It's one of those shibboleths and terms of art used by people in industry. If you go to trade-shows you'll hear it being used -- it's worth knowing if nothing else but for its sociological value among the data software tools crowd.
Side: it's a little like the word "inference" being used as a verb by folks in AI (example usage: we use GPUs to speed up model "inferencing") -- in AI, to inference means to "predict". It's a term of art. If someone with a traditional statistics background went to a deep learning conference, they are likely to be very confused because in traditional statistics, inference means to obtain parameters θ in a model y = f(x,θ), whereas in AI, inferencing refers to obtaining y.
"Provenance" just means where the data came from. [1]
It's one of those shibboleths and terms of art used by people in industry. If you go to trade-shows you'll hear it being used -- it's worth knowing if nothing else but for its sociological value among the data software tools crowd.
Side: it's a little like the word "inference" being used as a verb by folks in AI (example usage: we use GPUs to speed up model "inferencing") -- in AI, to inference means to "predict". It's a term of art. If someone with a traditional statistics background went to a deep learning conference, they are likely to be very confused because in traditional statistics, inference means to obtain parameters θ in a model y = f(x,θ), whereas in AI, inferencing refers to obtaining y.
[1] https://en.wikipedia.org/wiki/Data_lineage#Data_provenance