Data is often referred to as the “new oil,” but just like oil, it can have its imperfections, contamination, or flaws. One of the biggest challenges in data analytics today is bias — those systematic errors or imbalances in datasets that can lead to misleading conclusions, unfair decisions, and ethical dilemmas. Grasping the concept of data bias and figuring out how to tackle it is crucial for responsible and effective analytics.