Mehul Sheth

To have a high confidence in a product, testing it against a data set which resembles production data is must. The challenge is in generating data for testing that represents production. The data in production is not predictable, it doesn’t follow simple formula, there are many variables that characterize it. Broadly, test data can be divided into two categories: Arbitrary, which is random and unstructured and Realistic, which follows patterns, is predictable and controlled. To generate a Realistic test data, right patterns needs to be captured by analyzing the existing production data.