How did you analyze or prepare the data?
I cleaned the data by removing missing values and correcting errors. Then I organized the columns properly and created key calculations like total revenue, average spend, total visitors, and average rating.
I also used a visibility parameter to control which visuals are shown based on user selection, so the dashboard becomes more interactive.
After that, I analyzed the data to understand trends such as busy days, popular rides, and the impact of weather. Finally, I used these insights to build charts for better understanding and decision-making.
Who is the intended audience?
This dashboard is designed for:
Amusement Park Management
Operations Team
Marketing & Strategy Teams
Business Decision Makers
They can use it to:
Improve customer experience
Optimize ride operations
Increase revenue
What is your visualization about & problem it solves?
The dashboard provides a complete view of amusement park performance.
It helps identify:
Most popular rides (Bumper Cars, VR, etc.)
Revenue trends and top-performing centers
Customer segments (Age Group, Gender)
Wait time vs customer satisfaction
Weather and day impact on visits
Did you use Oracle Analytics AI features?
Yes, I used:
Auto Insights (AI-driven visualization suggestions)
Did you upload your visualization image and DVA file?
Yes, I uploaded
Example AI Prompts for this Data set
Prompt 1 – Revenue Insights
Analyze total revenue trends and identify key drivers influencing revenue across cities, ride types, and customer segments.
Prompt 2 – Ride Performance
Identify the most popular rides and analyze how wait time impacts customer ratings and ride usage.
Prompt 3 – Customer Behavior
Segment customers by age group and gender to understand spending patterns and visit frequency.
Prompt 4 – External Factors
Analyze how weather and day type (weekend vs weekday) impact visitor count and revenue.
Prompt 5 – Profitability
Evaluate the impact of discounts on final revenue and identify optimal discount ranges.
