Random data generation is useful for several purposes and plays a significant role in performance testing. This technique is also useful for generating synthetic data that can be used for various simulation experiment purposes. In fact, it is randomness that facilitates an unbiased sample selection from a large dataset.
We will look at random data generation with some specific properties:
- Pseudorandom with no specific distribution
- Normal distribution
- Poisson distribution