1. Which dataset did you use?

Bloomberg Historical Data (2024 – 2025)

2. How did you analyze or prepare the data?

Data Flow and Auto-Insights

3. Who is the intended audience for your visualization?

Intended audience is investment professionals (portfolio managers, risk committees, etc.) seeking a concise, cross-asset view of market dynamics related to the April 2025 volatility event that occurred across global financial markets.

4. What is your visualization about, and what question or problem does it address?

This dashboard is designed to communicate key correlations and shifts (identified by Oracle Analytics AI features) related to U.S. large and small-cap equities, developed ex-U.S. dividend-yielding equities, and Treasury yields - highlighting how these instruments interacted before, during, and after the volatility shock. The goal is to provide an institutional-grade, data-driven perspective on regime shifts, relative risk, and cross-market capital flows - enabling timely and actionable insights related to portfolio allocation, risk management, and macro-level decision-making.

5. Did you use any Oracle Analytics AI features when building your visualization (ex. AI Assistant)? If so, please describe how they were used

Explain, One-Click Analytics (Forecast, Trend, Reference), and AI Assistant