Women's Clothing Store Sales Performance Dashboard

User_QVE0A

1. Which dataset did you use?
   I developed a Women’s Clothing dataset and used it to design an interactive dashboard.
   
2. How did you analyze or prepare the data?
   I analyzed each attribute and measure with different visualizations, Understood the relationship between them and chose the best visualizations.
   
3. Who is the intended audience for your visualization?
   The sales team analyzes revenue and profitability performance across categories and brands.
   
4. What is your visualization about, and what question or problem does it address?
   This dashboard analyzes women’s clothing sales performance and delivers actionable insights to improve monthly and yearly profitability across brands and categories.
   
5. Did you use any Oracle Analytics AI features when building your visualization (ex. AI Assistant)? If so, please describe how they were used
   Yes, I leveraged an automated insight on revenue performance by category and brand and customized it to better fit the analysis requirements.
   
   Women_Clothing_Store.dva
6. Did you upload your visualization image and dva file?
   Yes, Completed!

Gopal Chopperla

A very well‑architected dashboard that clearly surfaces stable performance, diversified revenue drivers, and strong category profitability through intuitive, scalable visual design

Bhaskar Konar

This is a beautifully designed and well-structured dashboard!

The layout is clean and intuitive, with a great balance between visuals and data. I especially like the consistent theme and the creative use of fashion silhouettes to represent profit by category - it makes the dashboard both informative and visually engaging. The filters are well-placed, and the mix of trend, regional, and category views provides a complete performance snapshot.

Great work - professional, insightful, and aesthetically appealing! 👏

ALLARI HARIKA

Great job! Your hard work really shows. Proud of you!

User_QVE0A

Thank you @Gopal Chopperla , @Bhaskar Konar and @User_7V4L1 for the kind appreciation.