CMDB Data Quality Management

Overview

A CMDB is only as valuable as its data quality. Poor data leads to failed changes, incorrect impact analysis, and loss of trust. This skill covers:

• Measuring data quality KPIs (completeness, accuracy, consistency)
• Detecting and resolving duplicate CIs
• Identifying and managing stale/orphan records
• Implementing reconciliation processes
• Establishing ongoing data governance

When to use: During CMDB health assessments, before major changes, as part of regular maintenance, or when CMDB trust is low.

Value proposition: High-quality CMDB data can reduce change failure rates by 50%, decrease incident resolution time by 30%, and improve audit compliance.

Prerequisites