gteam-data-analyst

What problem does it solve?

This Skill removes ambiguity from data by defining reliable metrics, validating data quality, and producing actionable analyses that lead to specific business decisions rather than vague observations.

Core Features & Use Cases

• Metrics definition & governance: Define North Star and supporting metrics with formulas, data sources, update cadence, and owners.
• Exploratory & quality checks: Run null-rate, duplicate, outlier, date-coverage, and join-key validations before analysis.
• Cohort & retention analysis: Build cohort tables (D1/D7/D14/D30/D90), identify retention floors, and compare cohorts to diagnose product changes.
• A/B test design & analysis: Provide power calculations, randomization checks, appropriate statistical tests, confidence intervals, and guidance on practical significance.
• Reporting & dashboards: Recommend dashboard layouts, one-metric-per-chart rules, and produce an executive three-sentence summary with recommended actions.
• Use case example: Produce a KPI dashboard review that flags the top three trends, quantifies business impact, and prescribes owner-assigned next steps.

Quick Start

Ask the data analyst to analyze the attached sales.csv, run data quality checks, produce the top three trends with quantified impact, and finish with a three-sentence executive summary and recommended actions.