In practice, how often is sorting + binary search preferred over linear search?

I timed the function quicksort_strings.py with output to file sorted.txt, and that function itself took longer than linear_search.py by about a sixth of a second for the hundred thousand names. So, together, sorting the file then using binary_search.py is definitely slower than linear_search.py when trying to find the hundred names in a list of hundred thousand names.

Additionally, the Big-O notation of time complexity for quicksort is O(n*log(n)), which is larger than that for linear search (O(n)). So, would the time complexity for sorting then performing binary search be n*log(n) + log(n)?

In other words, although binary search per se is quicker and has a smaller time complexity than linear search, wouldn't it be slower and have a larger time complexity in practice because it requires sorting in order to work at all?

Supposing that you can't be sure your data is sorted, how large of a pool to search in and/or how many targets to look for would make sorting then using binary search faster than just using linear search on the unsorted data?

In practice, how big is big data--that is, how often do we encounter cases in which sorting + binary search is faster than linear search without sorting?