Retail sales analysis project focused on evaluating store performance, identifying sales trends, validating data quality, and communicating business findings through an executive dashboard.

Tools: Microsoft Excel · Google Sheets · Pivot Tables · Lookup Functions · Data Validation · KPI Analysis · Dashboard Design

Project Context

Retail companies generate large volumes of sales data across stores, departments, and weekly periods. Without a structured analysis, it can be difficult to identify which locations drive performance, how sales change over time, and where potential data-quality issues may affect business conclusions.

This project analyzed Walmart weekly sales data from 2012 together with store-level information. The objective was to transform raw spreadsheet data into a clear executive view of sales performance, store characteristics, and relevant business trends.

Business Objective

The objective was to build an executive sales dashboard that could:

• Measure total and average weekly sales.
• Compare performance across stores and departments.
• Identify the strongest- and weakest-performing locations.
• Evaluate sales trends throughout the year.
• Incorporate store characteristics to provide additional business context.
• Validate the data before reporting results by checking missing values, negative sales, unmatched records, and invalid store-size information.

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🔎 Key Analytical Questions

Which stores and departments generated the highest sales in 2012?

How did weekly sales change throughout the year?

Were there any data-quality issues that could affect the reliability of the dashboard and its conclusions?

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Dataset & Data Quality

Dataset

The analysis used two related datasets: