Quantitative data is data that can be measured numerically. Things that can be measured precisely -- rather than through interpretation -- such as the number of attendees at an event, the temperature in a given location, or a person's height in inches can be considered quantitative data. Its foil -- qualitative data -- requires a subjective decision in order to be categorized or measured.
Chris Deiner, SVP analytics at AbsolutData, on Quantitative Data:
Quantitative Data is objective data produced through a systematic process that is verifiable, replicable and in and of itself is not subject to interpretation. I contrast it with qualitative data, which is more subjective in nature and generally represents a quantification or assemblage of interpretations by a human layer.
Let's take as an example a set of interviews. While the bits and bytes of the digitization of the interviews may be quantitative data, data that can be text-mined, the combining of a handful of interviews and interpretation of the "meaning" thereof would generate qualitative data. The human interpretation of social-media text feeds to identify themes would be a process that generates qualitative data -- the interpretations. My definition comes from my original training in the field of market research where there is a well-known delineation between quantitative and qualitative research.