The data needed increases a lot the moment you have time dimension to anything. But as nobody seems to want to come up with an example, from something I have experience with, lets say you're running a shipping & logistics company. All your vehicles, trailers etc. have sat-nav, wireless broadband, sensor arrays for temperatures, weather, heck maybe even a video feed or two. But I'll stick into a "small" example.
The vehicle control-buses alone can generate thousands of messages per second, but if you don't want to go overboard, you might be tracking maybe 64 values on per-second basis. Oh, and naturally you have hundreds of trucks in the fleet, say you're a relatively small operator with 250 trackable vehicles. At bare minimum you're looking at something like vehicle-id, timestamp, flags and data per each item. This would be roughly 2k per row on a naive database, or half a megabyte for whole feet. Times the seconds, coming to whopping 14 gigabytes per day even if they're only in use 8 hours a day on average. In a year, you'll amass 5 terabytes of data.
If you're said logistics company, you probably want to outsource it somewhere, the company may be handling data from dozen or so logistics companies and then it's 60 terabytes per year. It might be desirable to save that data for 5 years, at which point you'd looking at 300 terabytes in active storage, from whence you'll want answers like "Who was driving on 5th Street on the new year's eve" or "Was the temperature of the cargo over 10C at any point during shipment XYZ" to the utterly complex data-mining for fuel economy etc.
Of course, in reality the amount of data you'd want to store would vary widely, you would also store much other data from administrative to legal, have different storage approaches for different uses, and employ different compression schemes starting with storing only when values change, but that's primarily an example of how the amount of data easily balloons once you figure in matters of scale and time-dimension. Even in something as simple as getting fresh bread delivered to your local store. I can imagine quite a few businesses having similar situation, especially as society gets more and more data-driven, which I guess is what this article is supposed to be about.