The necessity of comprehending the data and its limits is demonstrated by Simpson’s Paradox. As the world moves towards datasets gathered in extremely short spans of time, it reminds us of the importance of critical thinking when dealing with data, as well as looking for hidden biases and variables in the data. If the data is not stratified deeply enough, the Simpson paradox may exist. Even though the variation becomes modest, too much aggregation becomes irrelevant and produces bias. However, there will be insufficient data or information to identify the underlying pattern if we disaggregate too much. The variance has increased, but the bias has decreased. As a result, the Simpson Paradox can be considered the pinnacle of the Bias and Variance Trade-off.