---
name: data-analysis
description: Analyze datasets and extract insights. Use when exploring data, creating
  reports, or identifying patterns and trends.
metadata:
  source: nuday
  catalog: platform
  category: data
  priority: '25'
---

# Data Analysis

## Overview
This skill enables comprehensive data analysis and insight extraction.

## Analysis Process

### 1. Data Understanding
- Review data schema and types
- Identify key variables
- Check data quality
- Note data sources and collection methods

### 2. Exploratory Data Analysis
- Summary statistics (mean, median, std)
- Distribution analysis
- Missing value assessment
- Outlier detection
- Correlation analysis

### 3. Data Cleaning
- Handle missing values
- Remove duplicates
- Fix data types
- Standardize formats
- Address outliers

### 4. Analysis Techniques

#### Descriptive Analysis
- Central tendency measures
- Variability measures
- Frequency distributions
- Cross-tabulations

#### Trend Analysis
- Time series patterns
- Seasonal variations
- Growth rates
- Moving averages

#### Comparative Analysis
- Group comparisons
- A/B test results
- Benchmark comparisons
- Variance analysis

### 5. Visualization
- Choose appropriate chart types
- Use clear labels and legends
- Highlight key findings
- Maintain consistent styling

## Output Format
Provide analysis results as:
1. **Executive Summary**: Key findings in 2-3 sentences
2. **Detailed Findings**: Data-backed insights
3. **Visualizations**: Relevant charts/graphs
4. **Recommendations**: Actionable next steps