Description: Gaps or missing data points in a dataset are elements that are not present and can significantly influence analysis and reporting. These gaps can arise for various reasons, such as errors in data collection, technical issues, or simply because the information was unavailable at the time of capture. The presence of gaps can distort the results of an analysis, leading to incorrect conclusions or underestimating important trends. In the context of data processing and analysis, it is crucial to identify and manage these gaps to ensure data quality. Techniques for addressing gaps include data imputation, where missing values are estimated, or the removal of incomplete records. Proper management of gaps is essential to maintain data integrity and ensure that analyses are accurate and reliable.
