# Data Analytics Foundations

> Core data analytics concepts, Excel/Google Sheets fundamentals, and data collection techniques

- Skill: `majiayu000/data-analytics-foundations` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/data-analytics-foundations`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/data-analytics-foundations/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/data-analytics-foundations

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# Data Analytics Foundations Skill

## Overview
Master the foundational concepts of data analytics including data types, collection methods, spreadsheet fundamentals, and basic data manipulation techniques.

## Core Topics

### Data Fundamentals
- Understanding data types (quantitative, qualitative, structured, unstructured)
- Data sources and collection methods
- Data quality dimensions (accuracy, completeness, consistency, timeliness)

### Spreadsheet Proficiency
- Excel fundamentals and advanced formulas
- Google Sheets collaboration features
- Data cleaning and transformation in spreadsheets
- Pivot tables and data summarization

### Data Collection
- Survey design and implementation
- Web scraping basics
- API data extraction
- Database querying fundamentals

## Learning Objectives
- Understand core data analytics terminology and concepts
- Master Excel and Google Sheets for data analysis
- Implement effective data collection strategies
- Apply data quality assessment techniques

## Error Handling

| Error Type | Cause | Recovery |
|------------|-------|----------|
| Formula error | Invalid syntax | Validate formula structure |
| Data type mismatch | Wrong input format | Convert data types explicitly |
| Missing data | Incomplete dataset | Apply imputation or filtering |
| Performance issue | Large dataset | Use data sampling or optimization |

## Related Skills
- databases-sql (for advanced data querying)
- statistics (for data analysis techniques)
- visualization (for presenting insights)