How to Clean and Prepare Data in Excel: A Beginner's Walkthrough

Excel remains one of the most widely used tools for data entry, validation, cleaning, and analysis, making it a practical starting point for aspiring data analysts. A fictional laboratory dataset of roughly 50 records was used to demonstrate common data quality issues, including missing values, duplicate entries, inconsistent gender labels, and irregular facility and county names. Missing values were identified using Excel's filter function and manually corrected, while the built-in Remove Duplicates feature under the Data tab successfully flagged and removed one duplicate patient record. Inconsistent text entries, such as varied capitalizations of county names and gender abbreviations, were standardized using Excel's Find and Replace tool. The exercise highlights how basic Excel features can systematically resolve real-world data quality problems before any meaningful analysis begins.