Yes, the benchmarking database contains enough data to provide an accurate result. However more important to accuracy is the quality of the data.

When using machine learning (Bayesian statistical model) the quality of the data is paramount to be able to “train” the algorithm to learn from each new data set introduced.

When your data set is benchmarked, it is not just compared to a large volume of random data. It is referencing data that has been carefully selected over many years to enable the machine learning algorithm to understand what good and bad looks like across all measures within the system. This is what is refer to as using prior data to build new knowledge to apply to your analysis.