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analyze-data

Analyze data with hypothesis testing and root-cause investigations via postgres-mcp.

Updated Feb 24, 2026
Search Tags:#data#visualization#statistics#hypothesis#analyze#root-cause#prescriptive
One-click install
npx skills add https://github.com/modus-bi/dtp-bi-dashboards --skill analyze-data-modus-bi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: analyze-data
Source: https://github.com/modus-bi/dtp-bi-dashboards/tree/main/skills/analyze-data
Command: npx skills add https://github.com/modus-bi/dtp-bi-dashboards --skill analyze-data-modus-bi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill conducts comprehensive data analysis to transform raw data into actionable Level 4 insights, including hypothesis testing, correlation discovery, root-cause analysis, and quantified business recommendations.

Core Features & Use Cases

  • 🔍 Data exploration and profiling via postgres-mcp (PostgreSQL/ClickHouse)
  • 📊 Hypothesis testing and statistical significance to validate changes
  • 🔗 Correlation and pattern discovery across metrics
  • 🧭 Root Cause Analysis to identify primary drivers
  • 💡 Actionable recommendations with quantified impact
  • 🧭 Use Case: when asked to "analyze", "find the cause", "test a hypothesis", or "derive recommendations" from data

Quick Start

Run a guided data-analysis session on your dataset to produce prescriptive recommendations with quantified impact.

Frequently Asked Questions about analyze-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find the root cause of a sudden change in my business metrics?▼

Root cause analysis identifies primary drivers behind metric changes by running hypothesis testing and correlation discovery on your dataset. It transforms raw metrics into quantified explanations, pinpointing exactly what variables caused the observed shift.

What is the best way to test a hypothesis on my PostgreSQL data?▼

Hypothesis testing on PostgreSQL data validates whether observed metric changes are statistically significant. The process connects to your database, formulates statistical tests, and confirms or rejects hypotheses to ensure data-driven accuracy.

How do I turn data analysis into actionable recommendations with quantified impact?▼

To get actionable recommendations with quantified impact, run an end-to-end workflow that includes data exploration, correlation discovery, and root cause investigation. This yields structured Level 4 insights, translating findings directly into prescriptive actions.

Can I run statistical analysis and data visualization directly on a ClickHouse database?▼

Yes, statistical analysis and data visualization work directly with ClickHouse databases. The process profiles your data in place, runs correlation discovery, and generates visualizations to diagnose data-driven business problems without requiring manual data extraction.

When do I need prescriptive analytics instead of just descriptive reporting?▼

You need prescriptive analytics when descriptive reporting is insufficient and you must diagnose why metrics changed, test hypotheses, or derive actionable recommendations. It moves beyond showing what happened to providing structured, quantified business actions.

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