Empty cells in a dataset can significantly affect the concatenation process. When merging data sets, empty cells impact the overall accuracy and completeness of the resultant output. Concatenating non-empty data without considering those which are empty leads to errors when interpreting or analyzing the final consolidated dataset. Therefore, removing all empty cells or their inputs identified before performing concatenation is essential. Various spreadsheet software offers tools for identifying and managing blank cells while concatenating datasets. Working with datasets containing empty cells requires extra caution in ensuring data quality, especially where missing values are not directly addressed within the original dataset documentation or already handled through suitable data cleaning processes.