Why is it important to remove duplicates in data analysis?

Removing duplicates in data analysis is crucial because duplicates can distort results, leading to unreliable conclusions. When the same data points are counted multiple times, they can skew averages, totals, and other statistical metrics, resulting in an inaccurate representation of true trends and patterns in the data. This can mislead decision-making processes since analyses based on flawed data can lead to incorrect insights.

Therefore, ensuring that the data is free from duplicates helps maintain the integrity of the analysis, providing a clearer picture of the situation being studied. By working with unique values, analysts can draw more accurate conclusions, make better predictions, and ultimately support more reliable decision-making. Maintaining accuracy in data analysis is key to achieving valid and actionable insights.