here are my answers. Spreadsheets are used in several cases:
1) When you have a small-to-medium-sized dataset (100m data points) and want to do a particular set of calculations or draw a particular set of conclusions from it just once or twice—so that the time invested in writing code in R or something similar is less than the time needed just to bung a few formulas into a spreadsheet and get your results. Once you get into analyses or processes that will be repeated many times, it makes more sense to write code.
2) Similar case, when you need to work with essentially tabular database data, but the operations you're performing (basic filtering, extracting records based on one or two criteria, just handing data from one person to the next) are either so simple or will be repeated so rarely that a MySQL database is overkill and just emailing a file back and forth is easier.
3) When you are working with data as a part of a team, and certain members of the team that are specialists in some areas related to the data, or (for example) members of the team that are doing your data collections, aren't particularly computationally expert. Spreadsheets are hard for laymen, but it's doable—a dozen or two hours of training and people can get a general, flexible grasp of spreadsheets and formulae. It takes a lot longer for someone to become basically proficient with R, MATLAB, MySQL, Python, etc., and you really want those specialists to just be able to do what they do to or with the data, rather than focusing their time and effort on learning computational tools. Spreadsheets are general purpose and have a relatively shallow learning curve relative to lots of other technologies, but they enable fairly sophisticated computation to take place—if inefficiently at times. They're like a lowest-common-denominator of data science.
We use Spreadsheets all the time in what we do, mostly as a transient form. The "heavy hitting" and "production" data takes place largely in MySQL and R, but there are constant temporary/intermediate moments in which data is dumped out as a CSV, touches a bunch of hands that are really not MySQL or R capable, and then is returned in updated form to where in normally lives.