One of the primary challenges in data manipulation is ensuring the accuracy and reliability of the data. This involves rigorous [data cleaning](#) to remove errors, duplicates, and inconsistencies. Another challenge is the heterogeneity of cancer data, which can vary significantly between different patients and types of cancer. Standardizing and normalizing this data is crucial for meaningful comparisons and analyses. Additionally, ethical considerations, such as patient confidentiality and data security, must be addressed.
