A data analyst receives four files that need to be unified into a single spreadsheet for further analysis. All of the files have the same structure, number of columns, and field names, but each file…

Merging (or joining) combines data horizontally based on common key columns, which is not suitable when the goal is to stack similarly structured data.

Appending, also known as unioning or stacking, is the correct method when combining datasets that have the same schema (structure, columns, field names) but represent different observations or records. This operation adds the rows from one dataset to the end of another, effectively consolidating them vertically into a single spreadsheet.

Parsing involves analyzing a string or data stream to extract components or interpret its structure, which is not the primary method for combining entire files.

Clustering is a machine learning technique used to group similar data points together, not a method for combining files into a single structure.