exploratory-analysis

What problem does it solve?

This skill provides a disciplined, phase-driven approach to exploring unfamiliar datasets, helping users uncover patterns, anomalies, and actionable questions without a pre-existing hypothesis.

Core Features & Use Cases

• Systematic, multi-vector exploration (temporal, segmentation, and relationship patterns) to reveal hidden patterns in data.
• Phase-based workflow (data familiarization, pattern discovery, anomaly investigation, insight generation, and question formulation) with structured checkpoints.
• Reusable templates and guidance that support consistent documentation, hypothesis generation, and planning next steps for data projects.
• Use cases include onboarding a new dataset, identifying anomalies, and preparing a prioritized set of follow-up questions for deeper analysis.

Quick Start

To begin, follow the five-phase process starting with Phase 1: Data Familiarization, and reference the included templates to structure your exploration.