1. Which dataset did you use?
I used a Coffee Sales transactional dataset that includes:

• Order details (Order ID, Date, Time)
• Product information (Coffee Name, Category)
• Sales metrics (Revenue, Quantity, Transaction Value)
• Time attributes (Hour, Day, Month, Quarter)

2. How did you analyze or prepare the data?
Data preparation steps:

• Data Cleaning:
  • Removed null and duplicate records
  • Standardized coffee names and categories
• Feature Engineering:
  • Extracted Year, Quarter, and Month from the Order Date
  • Derived Hour and categorized Time of Day (Morning, Afternoon, Night)
  • Created calculated measures such as Total Revenue, Average Transaction Value, and Total Orders
• Aggregation:
  • Grouped data by coffee type, time of day, and quarter
• Data Modeling (in OAC):
  • Created measures and hierarchies
  • Enabled filters for dynamic data slicing

3. Who is the intended audience?
The dashboard is designed for:

• Business Executives / Store Managers
• Sales Managers
• Operations Teams

Purpose:

• Support quick decision-making
• Identify sales patterns
• Monitor overall performance

4. What is your visualization about, and what problem does it address?
This is a Coffee Sales Performance Dashboard that answers key business questions:

• Which coffee products generate the most revenue?
• What time of day drives the highest sales?
• Are sales improving across quarters?
• What are the peak sales periods?

Problem it addresses:

• Limited visibility into sales trends and customer behavior
• Helps optimize:
  • Product strategy
  • Staffing during peak hours
  • Sales performance tracking

5. Did you use Oracle Analytics AI features?
Yes, I utilized Oracle Analytics AI features:

• Built visuals like Revenue vs Hour of the Day and Peak Coffee Sales Times using Auto Insights, with further refinements
• Enabled the AI Assistant for the dataset, allowing users to ask natural language questions and receive automated insights

6. Did you upload your visualization image and DVA file?
Yes:

• The dashboard image has been prepared for presentation
• The DVA (Data Visualization Application) file is available for:
  • Reusability
  • Interview demonstrations
  • Future enhancements
    CoffeeShopDashboard.mp4
    Coffee Sales Analysis Dashboard.dva