1. Data Collection: Gathering data from reliable sources such as clinical trials, patient records, and laboratory experiments. 2. Data Cleaning: Removing or correcting inaccuracies, such as duplicate entries or incorrect values. 3. Data Validation: Checking data against predefined rules and standards to ensure it meets the required criteria. 4. Data Consistency: Ensuring that data is consistent across different datasets and sources. 5. Data Auditing: Regularly reviewing and auditing data to detect and correct potential errors.
