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DCH-33: Data Quality Operations

DCH 5 — Medium Protect

Mechanisms exist to check for Redundant, Obsolete/Outdated, Toxic or Trivial (ROTT) data to ensure the accuracy, relevance, timeliness, impact, completeness and de-identification of information throughout the information lifecycle.

Renumbered: Formerly DCH-22 in SCF 2025.4.

Control Question: Does the organization check for Redundant, Obsolete/Outdated, Toxic or Trivial (ROTT) data to ensure the accuracy, relevance, timeliness, impact, completeness and de-identification of information throughout the information lifecycle?

General (16)
Framework Mapping Values
AICPA Privacy Management Framework (PMF) M1.0-POF7
AICPA TSC 2017:2022 (used for SOC 2) (source) CC2.1 CC2.1-POF4 CC2.1-POF8
COBIT 2019 APO11.01 APO11.02 APO11.03 APO11.04 APO11.05 APO14.06 APO14.07 BAI08.04
COSO 2013 13.0
ISO 42001 2023 A.7 A.7.2 A.7.3 A.7.4 A.7.5 A.7.6
NIST 800-37 R2 TASK P-13
NIST 800-53 R4 DI-1
NIST 800-53 R5.2 PM-22 SI-18 SI-18(01)
NIST 800-53B R5 (privacy) (source) PM-22 SI-18
NIST 800-82 R3 PM-22 SI-18 SI-18(01)
NIST 800-82 R3 LOW OT Overlay PM-22
NIST 800-82 R3 MODERATE OT Overlay PM-22
NIST 800-82 R3 HIGH OT Overlay PM-22
NIST 800-161 R1 PM-22
NIST 800-161 R1 Level 1 PM-22
NIST 800-161 R1 Level 2 PM-22
US (3)
Framework Mapping Values
USA Federal CMS MARS-E 2.0 DI-1 DI-1.a DI-1.b DI-1.c DI-1.d
USA California CCPA 2025 7023(c)
USA Texas DIR SCSC 2.2 2025 PM-22
EMEA (1)
Framework Mapping Values
EMEA EU AI Act Article 10.3 Article 17.1(f)

Capability Maturity Model

Level 0 — Not Performed

Practices are non-existent, based on the inability to demonstrate an implemented and operational capability. A reasonable person would conclude the control is not being performed.

Level 1 — Performed Informally

SCR-CMM Level 1 criteria definitions are not available for this control: ▪ A reasonable person would conclude this control requires a structured process. ▪ At this level of maturity, the "ad hoc" nature of performing a capability informally would indicate the intent of the control is not met due to a lack of consistency and formality.

Level 2 — Planned & Tracked

SCR-CMM Level 2 criteria definitions are not available for this control: ▪ A reasonable person would conclude a well-defined and standardized process is required. ▪ At this level of maturity, the “requirements-driven” nature of performing the control is focused on a localized and/or regionalized implementation, not uniform and consistent across the organization. ▪ Requirements are narrowly scoped for applicability and are primarily derived from compliance obligations (e.g., laws, regulations and contracts).

Level 3 — Well Defined

Data Classification & Handling (DCH) capabilities are standardized across the entity for applicability to People, Processes, Technologies, Data and/or Facilities (PPTDF) to ensure consistency for Technology Assets, Applications, Services and/or Data (TAASD). Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Policies and standards associated with DCH domain capabilities are formally documented and centrally-managed by the entity's Governance, Risk & Compliance (GRC) team, or similar function. ▪ Standardized Operating Procedures (SOP) associated with DCH domain capabilities are well-documented and kept current by process owners. ▪ A Governance, Risk & Compliance (GRC) team, or similar function, is appropriately staffed and supported to implement and maintain DCH domain capabilities. ▪ Technology is leveraged to enhance the efficiency and accuracy of data classification and handling operations (e.g., GRC platform). ▪ The entity's Governance, Risk & Compliance (GRC) team, or similar function, works with business stakeholders and process owners to appropriately scope and reasonably implement cybersecurity and data protection controls associated with DCH domain capabilities to address Minimum Compliance Requirements (MCR) (e.g., applicable statutory, regulatory and/or contractual requirements) and Discretionary Security Requirements (DSR) (e.g., entity-required controls). ▪ An implemented and operational capability exists to check for Redundant, Obsolete/Outdated, Toxic or Trivial (ROTT) data to ensure the accuracy, relevance, timeliness, impact, completeness and de-identification of information throughout the information lifecycle.

Level 4 — Quantitatively Controlled

Data Classification & Handling (DCH) capabilities, in addition to being standardized across the entity and centrally managed to ensure consistency across Technology Assets, Applications, Services and/or Data (TAASD), efforts are metrics driven to provide sufficient insight for decision makers to predict optimal performance, ensure continued operations and/or identify areas for improvement. Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational. ▪ Metrics reporting includes quantitative analysis of Key Performance Indicators (KPIs). ▪ Metrics reporting includes quantitative analysis of Key Risk Indicators (KRIs). ▪ Scope of metrics, KPIs and KRIs covers organization-wide cybersecurity and data protection controls, including functions performed by third-parties. ▪ Organizational leadership maintains a formal process to objectively review and respond to metrics, KPIs and KRIs (e.g., monthly or quarterly review). ▪ Based on metrics analysis, process improvement recommendations are submitted for review and are handled in accordance with change control processes. ▪ Business and technical stakeholders are involved in reviewing and approving proposed changes to evolve capabilities.

Level 5 — Continuously Improving

Data Classification & Handling (DCH) capabilities, in addition to being standardized across the entity and centrally managed to ensure consistency across Technology Assets, Applications, Services and/or Data (TAASD), efforts are metrics driven to provide sufficient insight for decision makers to predict optimal performance, ensure continued operations and/or identify areas for improvement. Capability criteria associated with this control reasonably expect the following criteria to exist: ▪ Applicable SCR-CMM Level 3 (Well Defined) capabilities are implemented and operational. ▪ Based on predictive analysis, process improvements are implemented according to “continuous improvement” practices that affect process changes. ▪ Stakeholders make time-sensitive decisions to support operational efficiency, which may include automated remediation actions via Artificial Intelligence (AI) or Machine Learning (ML) technologies.

Assessment Objectives

  1. DCH-33_A01 organization-wide policies for Personal Data (PD) quality management are developed and documented.
  2. DCH-33_A02 organization-wide procedures for Personal Data (PD) quality management are developed and documented.
  3. DCH-33_A03 the policies address reviewing the accuracy of Personal Data (PD) across the information life cycle.
  4. DCH-33_A04 the policies address reviewing the relevance of Personal Data (PD) across the information life cycle.
  5. DCH-33_A05 the policies address reviewing the timeliness of Personal Data (PD) across the information life cycle.
  6. DCH-33_A06 the policies address reviewing the completeness of Personal Data (PD) across the information life cycle.
  7. DCH-33_A07 the procedures address reviewing the accuracy of Personal Data (PD) across the information life cycle.
  8. DCH-33_A08 the procedures address reviewing the relevance of Personal Data (PD) across the information life cycle.
  9. DCH-33_A09 the procedures address reviewing the timeliness of Personal Data (PD) across the information life cycle.
  10. DCH-33_A10 the procedures address reviewing the completeness of Personal Data (PD) across the information life cycle.
  11. DCH-33_A11 the policies address correcting or deleting inaccurate or outdated Personal Data (PD).
  12. DCH-33_A12 the procedures address correcting or deleting inaccurate or outdated Personal Data (PD).
  13. DCH-33_A13 the policies address disseminating notice of corrected or deleted Personal Data (PD) to individuals or other appropriate entities.
  14. DCH-33_A14 the procedures address disseminating notice of corrected or deleted Personal Data (PD) to individuals or other appropriate entities.
  15. DCH-33_A15 the policies address appeals of adverse decisions on correction or deletion requests.
  16. DCH-33_A16 the procedures address appeals of adverse decisions on correction or deletion requests.
  17. DCH-33_A17 the frequency at which to check the accuracy of Personal Data (PD) across the information life cycle is defined.
  18. DCH-33_A18 the frequency at which to check the relevance of Personal Data (PD) across the information life cycle is defined.
  19. DCH-33_A19 the frequency at which to check the timeliness of Personal Data (PD) across the information life cycle is defined.
  20. DCH-33_A20 the frequency at which to check the completeness of Personal Data (PD) across the information life cycle is defined.
  21. DCH-33_A21 the accuracy of Personal Data (PD) across the information life cycle is checked frequency.
  22. DCH-33_A22 the relevance of Personal Data (PD) across the information life cycle is checked frequency.
  23. DCH-33_A23 the timeliness of Personal Data (PD) across the information life cycle is checked frequency.
  24. DCH-33_A24 the completeness of Personal Data (PD) across the information life cycle is checked frequency.
  25. DCH-33_A25 inaccurate or outdated Personal Data (PD) is corrected or deleted.
  26. DCH-33_A26 automated mechanisms used to correct or delete Personal Data (PD) that is inaccurate, outdated, incorrectly determined regarding impact or incorrectly de-identified are defined.
  27. DCH-33_A27 automated mechanisms are used to correct or delete Personal Data (PD) that is inaccurate, outdated, incorrectly determined regarding impact or incorrectly de-identified.

Evidence Requirements

E-DCH-17 Data Catalog & Data Quality Records

Documented evidence of a data catalog and data quality management activities for sensitive / regulated data.

Data Protection

Technology Recommendations

Micro/Small

  • Product / project management

Small

  • Product / project management

Medium

  • Product / project management

Large

  • Product / project management
  • Data governance program

Enterprise

  • Product / project management
  • Data governance program

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