Sales Analysis Dashboard - Retail Fashion (2017)

This is an end-to-end sales analysis using annual sales data from DQFashion to identify revenue drivers, seasonal patterns, and category performance  using Microsoft Excel and Power Pivot.

The process involved integrating multiple datasets — including sales transactions, product master data, branch information, price changes, and holiday calendars — into a relational data model. Power Query was used for data preparation, while DAX measures enabled dynamic calculations such as revenue, units sold, and holiday-specific performance.

The results are presented through an interactive dashboard, allowing users to explore sales trends by month, product category, branch, and holiday status.

👉 See here for full analysis & working files 

Key insights from the analysis include:

• Total revenue in 2017 reached Rp60.2 billion, reflecting strong overall sales performance. 

• A total of 236,746 units were sold, indicating consistent demand throughout the year. 

• Average daily revenue was approximately Rp165 million, with relatively stable performance on non-holiday days. 

• June recorded the highest monthly revenue, likely influenced by increased consumer spending ahead of the Eid al-Fitr holiday. 

• Sweater emerged as the top-selling product, while the Dress category contributed the highest total revenue. 

• Holiday sales accounted for only around 6% of total revenue, suggesting untapped potential for targeted holiday promotions. 

• Among all branches, Jakarta 1 consistently generated the highest revenue.

This project reflects my strengths in structured analysis, data modeling, and data storytelling — transforming complex datasets into clear visuals and insights that support business decision-making.