The primary challenges associated with data overlap include:
Data Redundancy: Redundant data can inflate the volume of information without adding value, making it more difficult to identify unique and significant findings. Misinterpretation: Overlapping data can lead to misinterpretation, particularly if the overlap is not recognized and accounted for, potentially resulting in erroneous conclusions. Statistical Analysis: Overlapping data can complicate statistical analysis, requiring more sophisticated techniques to differentiate between unique and redundant information.
