What is the definition of Data Scout?
Copying from the abstract I found here - read the paper for more insights:

In the year 2011, the CMS collaboration introduced the novel concept
of data scouting, allowing to take data that otherwise would be
rejected by the usual trigger filters. This special data flow, based
on event-size reduction, was created to maintain sensitivity to new
light resonances decaying to jets or muons, with very small online and
offline resources allocated to it. The challenges implied by this new
workflow and the solutions developed within the CMS experiment are
shown. This technique is now a standard ingredient for CMS data-taking
strategy. The present status of data scouting in CMS is presented.

I do not come from a Physics background, and hence I could not completely understand the context while reading the paper in the larger scheme of things. But atleast this gives you a heads up about what it is.
Coming to Data Mining, there are plenty of definitions you can find. My definition would be using raw data to find patterns or insights from large datasets. This could be done with the use of many algorithms from math, computer science or statistics.
Some data mining algorithms are k-nearestneighbor, k-means, naive bayes, and so on.
So what is the difference between data scouting and mining? In mining, you consider raw datasets and perform some operations. In scouting, if I am not wrong, you take the data discarded by some filters (do not know what these filters are) while performing some operation, and then considering that data to perform additional operations.