Big Data Bias Syndrome: Don’t Be a Victim!

When selecting data for unbiased analysis, it's important to differentiate between a dense data set that contains a large number of similar data points and the far more diverse data points present in the real world. The gaps in data formed by either the lack of data or the density of similar data points produce a condition known as data sparsity. Those gaps are filled in by machine-learning algorithms that can easily bring with them the kind of bias baggage outlined above.