Noisy Data

Noisy data refers to information that contains errors, inconsistencies, or irrelevant details that can obscure the true patterns or signals. It’s like static on a radio—making it harder to hear the clear transmission. In data analysis, noise can result from measurement errors, random fluctuations, or external factors that are not linked to the main subject being studied. Removing or accounting for noise is essential to improve the accuracy of insights and predictions derived from the data. Essentially, noisy data makes it more challenging to find meaningful patterns, but addressing it helps ensure more reliable results.