Transform raw data into actionable insights with expert-level statistical rigor, metric definitions, and decision-ready visualization guidance.
by
Iván
Data Analysis helps you move beyond simple arithmetic to make data-driven decisions with consistent analytical standards.
It follows a Methodology First approach to lock metric definitions, separate extraction from interpretation, and deliver decision-ready summaries.
Clarify the business question and intended decision before running analysis.
Use metric contracts to define KPIs, grains, and filters consistently.
Keep data pulls and analysis steps distinct to maintain statistical rigor.
Summarize findings with recommended actions and stakeholder-ready visuals.
Standardize KPI definitions, grains, and filters to ensure a single source of truth.
Verify sample sizes, comparison fairness, and effect significance.
Guidance on choosing the right visual for trend, distribution, or cohort questions.
Outputs formatted for stakeholders that lead with insights and recommended actions.
Specialized approaches for identifying and flagging unusual data points.
Investigate unexpected shifts in business metrics to find root causes.
Analyze A/B test results for statistical significance and practical impact.
Track retention curves and lifecycle trends over time.
Translate technical findings into high-level decision briefs.
npx clawhub@latest install data-analysisRun in your terminal, or click the Install button at the top of this page for one-click setup.
No. It provides methodology and guidance rather than direct database connectivity.
Yes. It includes chart selection logic for trends, distributions, and cohorts.
Yes. It includes a checklist for sample size, fairness, and effect significance.
No. The core workflow is local and does not require external keys.
Yes. It is designed to guide reporting workflows and spreadsheet automation with consistent metrics.