E-commerce Sales Data Cleaning & Preparation Using Microsoft Excel

This project focuses on cleaning and preparing raw E-commerce sales data to ensure accuracy, consistency, and reliability for further analysis.

Using Microsoft Excel, I performed several data cleaning tasks to transform messy, inconsistent data into a structured and analysis-ready dataset.

Key Tasks Performed:

- Removed duplicate records to eliminate data redundancy.

- Identified and handled missing and blank values.

- Standardized inconsistent text values.

- Corrected date formats and ensured consistency.

- Identified and corrected invalid numerical values.

- Removed unnecessary spaces and formatting inconsistencies.

- Reviewed the dataset to ensure data accuracy and consistency.

- Organized the final dataset into a clean and structured format.

Tools & Techniques:

- Microsoft Excel

- Remove Duplicates

- TRIM, CLEAN, PROPER, IF, IFERROR

- Find & Replace

- Conditional Formatting

- Data Validation

- Sorting and Filtering

Project Outcome:

Successfully transformed raw, unstructured sales data into a clean, organized, and analysis-ready dataset, providing a reliable foundation for business intelligence and data analysis.