course, I've also never heard of or touched the software you listed there either, but that may be because I don't view the data science and machine learning I'm interested in as being about specific software or vendor software...
sounds more database- lingo to me...
"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
Where I work, (a large pharmaceutical), these notebooks are taken very seriously by biologists, chemists, and chemical engineers, and increasingly are shaping the mindset of our data scientists (who have yet to adopt them).
Given the longstanding practice of documenting experiment design and method, I think it's probably long overdue that the exploratory analysis of experiment-based data must also adopt more rigorous governance to ensure that necessity and sufficiency are ensured when drawing inferences from experiment, especially when the data used was not originally intended to answer the current question posed.
A few publications from ~2011-2015 period:
http://ceur-ws.org/Vol-1558/paper37.pdf
https://ieeexplore.ieee.org/document/5739644
https://link.springer.com/chapter/10.1007/978-3-642-53974-9_...
Add a variety of additional links dating back a bit further (note the emphasis in this case on research data and tracking state of an experiment).
https://nnlm.gov/data/thesaurus/data-provenance
Data provenance is not a database / data warehouse term. It is uniquely and specifically a basic “101” concept of statistical science and ML / data science, where the custody and tracking of data are specifically tied to iterations of experiments, prototypes and research, for the sake of reproducibility.
If I was interviewing an experienced statistical researcher and they didn’t at least have a working knowledge of the core concepts, that would be a huge red flag.
Another poster mentioned vendor brochures and trade shows, which is in line with my expectations about which community it stems from, and also explains why I've never heard of it because I try to keep away from such environments these days.
Everywhere I've been the things which I take to make up "provenance" have generally been referred to under the simple label of "data quality", with separate subset definitions and measures such as timeliness, source, authority, format, history, suitability, verification, etc.
Of course, that's assuming people even worry about such things. In practice, let's be frank, anyone who's worked with data science knows they actually get shorter shrift than they deserve in practice: I'm probably among a minority of people in the real world who actually take things seriously, and I find myself on a constant crusade to remind people that just because a data point exists in a data set doesn't mean it's useful/ appropriate/ truthful/ unbiased.
data quality is a bit problematic, because I can see it being used by people who think provenance doesn't have any thing to do with quality, and from a variety of fields, but it is also infinitely more popular according to historical search trends, and in my last three jobs provenance would fall under the data quality framework.
I’ve worked as a data engineer for the last two years and never heard of this being used in this context before.
Typically the word “data lineage” is used to mean this in my experience.
I don’t think I’ve ever been in a meeting where someone mentioned provenance except referring to a show about paintings.
Lineage isnt the same thing, being a more specific technical term referring to keeping the history of datasets and where they came from (basically), but people actually say the words “data governance” and “lineage”.
