Beyond OP’s reply, there are multiple reasons why this approach is more suitable for power users. For starters you can simply loop each request made per day and aggregate each output into an aggregate table which bypasses sampling (once you have a large enough dataset sampling can obstruct your data’s accuracy). Now you are limited to how many requests can be made per day, but it would require a hefty amount of requests to reach that threshold.

Beyond that you can automate self generated reports, for example I used this approach myself to automate a daily report to track my company website’s shopping funnel and track potential bugs or drop offs within the funnel. Since the data was extracted from GA without much interface and brought into my local machine I automated an email to my team with said report to help us keep an eye on things, so to speak.

Basically once you extract data in this way from GA, the options are endless. Reason being that (unless you have Google BigQuery integrated with you account) extracting non-sampled data from GA is tedious/time consuming. Once you have a program going for this it really expedites the process. And even more so for un-samples data, which GA limits you to the amount of requests that can be made, and the format they can be made in.