Data Science & Analytics Topics
Statistical analysis, data analytics, big data technologies, and data visualization. Covers statistical methods, exploratory analysis, and data storytelling.
Data Visualization and Dashboard Design
Designing visuals and dashboards that communicate clearly. Covers chart-type selection, encoding choices, dashboard layout and hierarchy, avoiding misleading visuals, and designing for the intended audience and decision. Emphasizes effectiveness over decoration.
Data Storytelling and Insight Communication
Turning analysis into a persuasive, decision-ready narrative for non-technical stakeholders. Covers structuring an insight, translating statistical results into plain language, framing recommendations and trade-offs, and tailoring the message to the audience. Emphasizes driving action, not just presenting numbers.
Product and User Behavior Analytics
Analyzing how users actually behave in a product, from event data that already exists. Covers cohort construction and cohort analysis, retention curves and how to interpret their shape, engagement, stickiness and activation metrics, behavioral segmentation used as an analytical lens, funnel and conversion interpretation, and the statistical treatment of small or noisy cohorts, including churn and uplift modeling. The scope is reading and interpreting behavioral data, not instrumenting its collection, defining the metrics themselves, diagnosing why a specific metric moved, or attributing conversions to acquisition channels.