data-validation

What problem does it solve?

This Skill addresses the critical need for rigorous quality assurance in data analysis, preventing errors, biases, and inaccuracies from reaching stakeholders.

Core Features & Use Cases

• Pre-Delivery QA Checklist: Comprehensive checks for data quality, calculation logic, and reasonableness.
• Pitfall Identification: Educates on common data analysis mistakes like join explosions, survivorship bias, and incomplete period comparisons.
• Reproducibility Standards: Provides templates for documenting analyses and code to ensure others can replicate the work.
• Use Case: Before sharing a crucial sales performance report, use this Skill to run through the checklist, verify aggregation logic, and ensure no survivorship bias is present in the user segmentation.

Quick Start

Use the data-validation skill to run through the pre-delivery QA checklist on the attached analysis document.