This dashboard shows how drivers perform during a race using telemetry data. It highlights average speed, maximum speed, engine RPM, and total laps.
It also shows how speed changes across the track and compares throttle and brake usage to understand driving behavior. The dashboard helps identify fast sections, braking zones, and top-performing drivers.
The goal is to turn raw racing data into simple and useful insights for performance analysis.
- Which dataset did you use?
I used a custom F1 telemetry dataset created and uploaded as a CSV file in Oracle Analytics.
2. How did you analyze or prepare the data?
I explored the dataset using Oracle Analytics features like Explain (AI Insights), basic aggregations, and calculated measures. I also structured the data to focus on key metrics such as speed, throttle, brake, and driver performance.
3.Who is the intended audience for your visualization?
The intended audience is racing analysts, team strategists, and anyone interested in understanding driver performance and race behavior.
4. What is your visualization about, and what question or problem does it address?
This dashboard analyzes driver performance using telemetry data. It helps identify speed patterns across the track, compare drivers based on performance, and understand throttle and brake behavior to evaluate driving style and efficiency.
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 used the Explain (AI Insights) feature to analyze patterns and identify key drivers in the data. The AI Assistant feature was not available in my environment, as it required administrator access to enable.
6. Did you upload your visualization image and dva file?
Yes, I have uploaded both the visualization image and the DVA file.
