I'm not sure what the appropriate terminology is, but in trying to run simulations, I always find it tricky to create good fake data.
I don't have an particular application for this, but let's say I want to play around with some silly stock market predicting algorithm - if I were to just use a standard random number generator to get my test data, it would all hover around .5, even over short intervals, and this wouldn't really produce the kind of data that the stock market usually produces during the day (comparing it to stock charts). Even if the market closes with no gains or loses, you might still find volatility in the middle - simple random walks don't create those same effects.
I guess you could stack rngs on top of one another, a larger magnitude for a full day value, a smaller magnitude per hour, and magnitude still per second, summing them all together to get a more step-like pattern, but that's really too predicable - you know as a developer where those steps will be, or are likely to be if you randomize the durations.
You could literally simulate individual buyer and seller personalities, I guess, but that's a lot of work and computation. (As far as I know, real stock market data is not freely available in raw form)
So, might we go to find free, easily accessible, quick-flowing, "interesting" data?