GitHub
segmentation-analysis
Customer/user segmentation with actionable insights. Use when identifying distinct customer groups, analyzing segment-specific behavior, profiling high-value segments, or testing segmentation hypotheses.
Skills IA Documentation
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Catégories: Documentation
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stakeholder-requirements-gathering
Structured requirements elicitation for analysis requests. Use when scoping new analysis projects, clarifying ambiguous business questions, or documenting analysis acceptance criteria with stakeholders.
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root-cause-investigation
Systematic investigation of metric changes and anomalies. Use when a metric unexpectedly changes, investigating business metric drops, explaining performance variations, or drilling into aggregated metric drive...
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executive-summary-generator
Create concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats.
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funnel-analysis
Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, A/B testing funnel performance, or optimizing user journeys.
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visualization-builder
Create effective, publication-ready data visualizations. Use when choosing chart types, designing dashboards, creating presentation visuals, or building interactive visualizations with best practices.
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analysis-assumptions-log
Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
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analysis-qa-checklist
Pre-delivery quality assurance for analysis work. Use when reviewing analysis before sharing with stakeholders, checking for completeness, validating assumptions, or ensuring clarity of recommendations.
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insight-synthesis
Transform data findings into compelling insights. Use when converting analysis results into actionable insights, connecting findings to business impact, or preparing insights for stakeholder communication.
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schema-mapper
Database schema understanding and relationship mapping. Use when exploring unfamiliar databases, documenting table relationships, identifying join paths, or generating ERD documentation for existing schemas.
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metric-reconciliation
Cross-source metric validation and discrepancy investigation. Use when metrics from different sources don't match, investigating data quality issues between systems, or validating data migration accuracy.
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analysis-documentation
Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.
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analysis-planning
Structure analysis approach before starting work. Use when receiving new analysis requests, breaking down complex questions into steps, or planning iterative analysis workflows.
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ab-test-analysis
Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
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cohort-analysis
Time-based cohort analysis with retention and behavior tracking. Use when analyzing user retention over time, comparing cohort performance, identifying lifecycle patterns, or measuring feature adoption by cohor...
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technical-to-business-translator
Translate technical analysis into business language. Use when explaining statistical concepts to non-analysts, simplifying technical findings, or bridging communication between data teams and business stakehold...
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data-narrative-builder
Build compelling data-driven narratives and stories. Use when presenting analysis results, creating reports, or communicating data insights through storytelling frameworks.
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impact-quantification
Estimate and communicate business impact of insights. Use when sizing opportunities discovered in analysis, calculating ROI of recommended actions, or prioritizing initiatives by potential impact.
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programmatic-eda
Systematic exploratory data analysis following best practices. Use when analyzing any dataset to understand structure, identify data quality issues (duplicates, missing values, inconsistencies, outliers), exami...
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data-quality-audit
Comprehensive data quality assessment against defined business rules and constraints. Use when validating data against expected schemas, checking referential integrity across tables, or auditing data pipeline o...
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query-validation
SQL query review and validation for correctness, performance, and best practices. Use when reviewing queries for logical errors, optimizing query performance, checking for SQL anti-patterns, or validating busin...
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business-metrics-calculator
Standard business metric calculation with industry benchmarks. Use when calculating SaaS metrics (MRR, churn, LTV, CAC), e-commerce KPIs, or product analytics metrics with proper definitions.
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context-packager
Efficiently package context for AI-assisted analysis. Use when preparing to work with Claude on analysis, organizing context documents, or structuring prompts for complex analytical tasks.
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semantic-model-builder
Create comprehensive semantic layer documentation for analytics assets. Use when documenting data models, defining business metrics, creating data dictionaries, or building context for AI-assisted analysis.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.