Applied Data Analysis Lifecycle and Methodology

A clinical data analyst needed to identify true predictors of heart disease while controlling for demographic confounders. Moving beyond basic correlations, the analyst evaluated various data analysis models to isolate independent predictive power. The resulting dashboard features a horizontal bar chart ranking clinical variables by absolute coefficient magnitude, revealing 'Major Vessels' (1.076) and 'Thalassemia' (0.619) as top predictors, while conventional markers like 'Cholesterol' (0.236) ranked lower. A heatmap further visualizes male disease rates escalating from 40.7% to 100% across age bands. This visual evidence enabled a statistically defensible recommendation for updating triage protocols without relying on opaque spreadsheets.

What it shows:

Ranked feature discriminators and heatmaps provide clear visual evidence to challenge conventional assumptions.

A fundamental equity analyst generated a dashboard to compare financial metrics for two Swiss large-cap equities, ABB and UBS, directly from SEC JSON filings. The dashboard frames the differing balance-sheet models and presents a table of key metrics, such as ABB's $32.2B revenue (2023) and UBS's $1.62T total assets (2025). A multi-line scatter chart plots revenue trajectories, showing ABB peaking around $42B in 2013 and UBS dipping to roughly $18B in 2022. This workflow solves the manual burden of extracting, aligning, and visualizing disparate SEC filing data, demonstrating essential data analyst technical skills for portfolio review.

What it shows:

Automated extraction and alignment of complex financial filings accelerates comparative equity research.