Data disparity refers to the differences in data availability, quality, or representation among various datasets within analytical contexts. This discrepancy can lead to skewed insights, misinterpretation of data, and challenges in achieving accurate analyses. Data disparity often arises from issues related to data collection, format inconsistencies, and storage practices. Addressing data disparity is essential for ensuring reliable analytics, enabling organizations to make informed decisions based on comprehensive and accurate data evaluations.