ksb-d07-k0016

name	KSB-D07-K0016
description	Automated Data Validation: Machine learning algorithms detecting inconsistencies, anomaly detection for unusual patterns, predi...
version	1.0.0
domain	D07
domain_name	Spontaneous Reporting Systems
type	Knowledge
proficiency_level	L1
bloom_level	understand
triggers	["explain automated data validation","what is automated data validation","explain automated data validation"]
epa_mapping	EPA-02, EPA-04, EPA-05
cpa_mapping	CPA-02, CPA-05
regulatory_refs	FDA-CFR-002, ICH-E2C(R2), ICH-E2F, EMA-GVP-004

KSB-D07-K0016: Automated Data Validation

Overview

Domain: D07 - Spontaneous Reporting Systems Type: Knowledge Proficiency Level: L1 (Novice - Direct supervision required) Bloom Level: Understand

Description

Machine learning algorithms detecting inconsistencies, anomaly detection for unusual patterns, predictive validation rules

Context

• Major Section: Global Spontaneous Reporting System Architecture
• Section: AI-Enhanced Data Quality Management

EPA Mapping

• EPA-02:3004-3005
• EPA-04:3009-3010
• EPA-05:3011-3012

CPA Pathway

• CPA-02, CPA-05

Regulatory References

• FDA-CFR-002
• ICH-E2C(R2)
• ICH-E2F
• EMA-GVP-004

Instructions

When this skill is activated, Claude should:

1. Demonstrate L1 proficiency in automated data validation
2. Apply understand level cognitive skills to explain the topic
3. Reference relevant regulatory guidance (FDA-CFR-002, ICH-E2C(R2), ICH-E2F, EMA-GVP-004)
4. Connect to related EPAs: EPA-02, EPA-04, EPA-05

Key Competencies

• Machine learning algorithms detecting inconsistencies, anomaly detection for unusual patterns, predictive validation rules

Assessment Criteria

• Can explain core concepts independently
• Demonstrates understanding of regulatory context
• Applies knowledge appropriately to PV scenarios

Related Skills

• Other D07 skills in AI-Enhanced Data Quality Management
• Cross-domain integrations per DAG architecture

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Generated from PV KSB Framework v1.0 | 2025-12-31