# Data Quality and Integrity Controls One-sentence definition: Processes and checks that ensure data is accurate, complete, consistent, and reliable across its lifecycle. ## Key Facts - Dimensions: accuracy, completeness, consistency, timeliness, uniqueness. - Controls: validation rules, referential integrity, constraints, deduplication. - Reconciliation between sources; exception queues and stewardship. - Integrity verification: hashes, digital signatures, checksums (end-to-end). - Data quality metrics & SLAs tied to business impact. - **Verify:** check official (ISC)² CBK and current exam outline. ## Exam Relevance - Pick controls that prevent/identify corruption and stale data. **Mnemonic:** “**ACCT-U**” → Accurate, Complete, Consistent, Timely, Unique. ## Mini Scenario Q: Reports show duplicate customers—what control? A: Deduplication rules and unique key constraints. ## Revision Checklist - Name 3 data quality dimensions. - Give one preventive and one detective control. - Tie a metric to business impact. ## Related [[Hashing and Checksums for Data Integrity]] · [[Data Catalogs and Metadata Management]] · [[Master Data Management (MDM)]] · [[Data Warehouse and Data Lake Security]] · [[Logs and Telemetry as Sensitive Data]] · [[Domain 2 - Index]]