My rule-of-thumb is that if you have less than a terabyte of data, you're better off processing it locally, and even that is pretty conservative. Big data is for when you have problem sets that simply will not fit on a single machine. With 4TB hard drives going for about $60, a lot of problems are better solved by simple algorithms in efficient programming languages on a single box.

There are some data sets where you really do need big-data tools, but it's for when you have petabyte-scale data, not megabyte/gigabyte-scale data.