Identifying duplicate entries involves a systematic review of the dataset. Techniques include:
Manual Review: Physically inspecting the data for repetition, though this is often impractical for large datasets. Automated Tools: Using software tools and algorithms to detect duplicates based on predefined criteria such as patient ID, date of birth, or other unique identifiers. Data Cleaning: Implementing data-cleaning procedures to flag potential duplicates for further review.
