ksb-d08-k0021

name	KSB-D08-K0021
description	Automated Data Quality Assessment: Missing data imputation using machine learning, outlier detection algorithms, consistency validation...
version	1.0.0
domain	D08
domain_name	Signal Detection & Management
type	Knowledge
proficiency_level	L4
bloom_level	analyze
triggers	["explain automated data quality assessment","what is automated data quality assessment","analyze automated data quality assessment"]
epa_mapping	EPA-04, EPA-05
cpa_mapping	CPA-02
regulatory_refs	FDA-GUID-006, EMA-GVP-005, EMA-GVP-010, CIOMS-VIII

KSB-D08-K0021: Automated Data Quality Assessment

Overview

Domain: D08 - Signal Detection & Management Type: Knowledge Proficiency Level: L4 (Proficient - Independent practice) Bloom Level: Analyze

Description

Missing data imputation using machine learning, outlier detection algorithms, consistency validation across data sources

Context

• Major Section: Multi-Source Data Integration and Intelligence Synthesis
• Section: AI-Enhanced Data Quality and Signal Validation

EPA Mapping

• EPA-04:3009-3010
• EPA-05:3011-3012

CPA Pathway

• CPA-02

Regulatory References

• FDA-GUID-006
• EMA-GVP-005
• EMA-GVP-010
• CIOMS-VIII

Instructions

When this skill is activated, Claude should:

1. Demonstrate L4 proficiency in automated data quality assessment
2. Apply analyze level cognitive skills to analyze the topic
3. Reference relevant regulatory guidance (FDA-GUID-006, EMA-GVP-005, EMA-GVP-010, CIOMS-VIII)
4. Connect to related EPAs: EPA-04, EPA-05

Key Competencies

• Missing data imputation using machine learning, outlier detection algorithms, consistency validation across data sources

Assessment Criteria

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

Related Skills

• Other D08 skills in AI-Enhanced Data Quality and Signal Validation
• Cross-domain integrations per DAG architecture

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