This project demonstrates the most critical first step in any data analysis workflow: Data Cleaning and Preparation.
Using the Power Query Editor (in Excel or Power BI), I loaded a 'Bike Sales' dataset to begin the process of transforming it from raw data into a clean, analysis-ready format.
Key steps shown in this project:
Data Loading: The dataset was successfully imported into Power Query to start the ETL process.
Data Quality Assessment:
As shown, the "Column Quality" feature was enabled to profile the data.
This view identifies the percentage of Valid, Error, and Empty values in each column, which is essential for diagnosing data integrity issues.
Setting Data Types:
The data types for each column were correctly defined (e.g., Int64.Type for numbers, type date for dates) to ensure accuracy in all future calculations and visualizations
