Interactive Sales Dashboard Project

Introduction

This project showcases the application of advanced Excel techniques to transform raw sales data into an insightful, interactive dashboard. Designed during the Analytics Extra mentorship program, the project demonstrates data cleaning, visualization, and storytelling skills using Power Query and pivot tables.

Problem Statement

In today’s fast-paced business world, decision-makers require quick, actionable insights. The challenge was to:

1. Clean and structure a raw dataset for analysis.
2. Build dynamic visuals to track KPIs such as sales, profits, and top-performing states.
3. Enable interactivity through slicers for tailored insights.

Skills Demonstrated

1. Data Cleaning: Leveraged Power Query to preprocess and clean the dataset.
2. Data Analysis: Utilized pivot tables and calculated fields for detailed aggregations.
3. Data Visualization: Created insightful charts and cards to highlight key performance metrics.
4. Dashboard Design: Structured visuals for interactivity and aesthetics.

Data Overview

Dataset Fields:

• Identifiers: rowid, orderid, product id
• Order Details: order date, ship date, ship mode, customer id, customer name
• Geography: segment, country, city, state, postal code, region
• Product Details: category, sub category, product name
• Metrics: sales, quantity, discount, profit The dataset consisted of 9,994 transactions spanning four years (2014–2017).

Results and Analysis

Key Metrics

Metric Value

• Total Transactions 9,994
• Total Sales $2,292,669
• Total Quantity Sold 37,873 units
• Total Profit $286,397
• Total Discount $1,561

Dashboard Highlights

Cards

• Top Metrics
  • Total sales, transactions, profit, and discounts.
• Segment Quantities
  • Consumer - 5,191; Corporate - 3,020; Home Office - 1,783.

Visuals

• Line Chart
  • Month-to-month percentage profit changes (2015-2017).
• Bar Charts
• Product categories by profit and sales.
• Segment sales contribution.
• Donut Chart
  • Segment profit percentage contribution.
• Top 10 States by Sales.

Interactivity

• Slicers
  • Year (2014-2017)
  • Shipping mode
  • Region.

Conclusion

This project highlights the power of Excel in:

1. Cleaning and structuring large datasets.
2. Extracting actionable insights through interactive visuals.
3. Designing dashboards that improve decision-making.

Recommendations

1. Automation: Use VBA or Power Automate to update the dashboard with new data automatically.
2. Advanced Tools: Transition the dashboard to Power BI for greater scalability and richer visuals.
3. Customization: Implement additional filters (e.g., by product or customer demographics).

Future Outlook

The success of this project reflects growing proficiency in Excel and data visualization. Next steps include mastering Power BI and SQL for comprehensive business intelligence solutions as well as implementing the recommendations herein in upskilling journey.

Acknowledgments

Special thanks to the Analytics Extra mentorship program under Adewale Yusuf for guidance and support throughout this project.