data-analysis

Analyze structured business datasets to uncover trends, outliers, and correlations.

27|4|Updated Jun 12, 2025

Search Tags:#data #insights #statistics #trends #analyze #data-quality

Ready to run

npx skills add https://github.com/definableai/definable.ai --skill data-analysis-definableai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/definableai/definable.ai/tree/main/definable/definable/skill/library/data-analysis
Command: npx skills add https://github.com/definableai/definable.ai --skill data-analysis-definableai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze structured datasets to reveal insights, trends, and quality issues without manual trial-and-error.

Core Features & Use Cases

Statistical reasoning: compute descriptive and inferential statistics to summarize data and test hypotheses.
Quality assessment: identify data quality issues such as missing values, inconsistencies, and outliers.
Pattern discovery: detect trends, seasonality, correlations, and anomalies across dimensions.
Use Case: evaluate quarterly sales to identify drivers of growth and flag data quality concerns.

Quick Start

Provide a dataset and ask for a statistical summary of the key findings.

Frequently Asked Questions about data-analysis

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

FAQPage Schema

How do I analyze structured data to identify trends and outliers?▼

To analyze structured data for trends and outliers, the Skill applies statistical reasoning to compute descriptive and inferential statistics, detecting anomalies, correlations, and seasonality across dimensions while performing data quality checks.

What is the best way to find data quality issues in a tabular dataset?▼

Finding data quality issues in tabular datasets involves identifying missing values, inconsistencies, and statistical outliers. The Skill automates this quality assessment to reveal inconsistencies without manual trial-and-error.

Can I use statistical reasoning to evaluate quarterly sales and growth drivers?▼

You can evaluate quarterly sales and growth drivers by applying statistical reasoning to time-series data. The Skill uncovers comparative metrics and interpreted conclusions while explicitly noting sample size and data limitations.

Does this data analysis approach work with time-series and categorized datasets?▼

This data analysis approach works with time-series, tabular, and categorized datasets. It detects patterns, seasonality, and anomalies across dimensions, producing results with explicit time periods and interpreted conclusions.

What are the limitations of automated data insights for business datasets?▼

Limitations of automated data insights include potential confounders and data constraints. The Skill explicitly notes sample sizes, time periods, and data limitations in its interpreted conclusions to maintain analytical transparency.

How do I get a statistical summary of my dataset's key findings?▼

To get a statistical summary of key findings, provide your dataset and request analysis. The Skill computes descriptive and inferential statistics to summarize data, test hypotheses, and output actionable insights.