I have seen this term come up a fair amount in machine learning. My guess would be that gold data is data which has been manually tagged, rather than learned by some process. However, I'm not too sure. So, what is the meaning of this phrase?
I think you're probably referring to gold standard data. This refers to data of very high quality, which is more or less as close as you can get to the ground truth. For example, Alzheimer's disease can be diagnosed through behavioral tests, but it's not a perfect diagnosis and can be confused with other types of dementia. A definitive diagnosis Alzheimer's can be made by performing an autopsy on the brain, resulting in an unambiguous diagnosis about which there is no uncertainty. In this case, the autopsy diagnosis represents the gold standard test.
Gold standard data is great for machine learning tasks, since it is known to be of high quality, and avoids the "garbage in, garbage out" problem. If you want to build a model to predict Alzheimer's disease, you'd much rather have the brain autopsy data, since there will be no mislabeled data. Gold standard data may be hard to come by, however, due to it being difficult or expensive to obtain.