ICCP DGSP key terms

The decision-rights framework that specifies who may make which data decisions, how accountability is assigned, and how data use is monitored and enforced across the organization.

The day-to-day operational work of caring for data assets on behalf of others: defining terms, resolving quality issues, monitoring usage, and escalating decisions to accountable owners.

The accountable role with authority to approve access, classify the asset, and accept risk for a defined data domain; typically a business leader rather than a technical specialist.

A person assigned to a data domain who maintains definitions, investigates quality defects, coordinates remediation, and serves as the go-to contact for questions about that data.

The technical role that stores, moves, and protects data according to owner-approved rules, handling backups, access provisioning, and platform controls rather than business definitions.

The clear, documented assignment of answerability for a data asset's quality, protection, and appropriate use, so that no asset is unowned and decisions have a named decision-maker.

A logical grouping of related data (such as customer, product, or finance) used to scope stewardship assignments, policy application, and quality measurement.

A formal statement of mandatory rules governing data creation, access, use, retention, and disposal, approved at a level with authority to enforce it.

A specific, measurable requirement that supports a policy, such as a mandatory date format, allowed value set, or required metadata field for a data element.

A cross-functional decision body of business and technology leaders that sets priorities, resolves escalated data disputes, and approves policies and standards.

The documented design of how governance work flows: roles, decision rights, committees, escalation paths, and processes, whether centralized, federated, or hybrid.

A model in which central guidance sets common policy and standards while business units or domains make local decisions and carry stewardship responsibilities.

A controlled vocabulary of business terms with approved definitions, synonyms, and owners, used to align meaning across reports, systems, and teams.

A catalog of technical metadata for data elements, including names, data types, lengths, allowed values, and source system, describing how data is physically structured.

Structured information describing data itself, such as definitions, formats, ownership, lineage, sensitivity, and usage, enabling discovery, trust, and control.

An inventory and search tool that records available data assets with their metadata, owners, and classifications so users can find and assess suitable data.

A record of where data originates, how it is transformed, and where it flows across systems, supporting impact analysis, audit, and quality root-cause work.

Assigning data to sensitivity tiers (for example public, internal, confidential, restricted) so that handling, access, and protection controls match the risk.

A rule set stating how long each category of data must be kept to meet legal, regulatory, and business needs, and when it must be destroyed.

The controlled destruction or de-identification of data once its retention period ends or a legal hold is lifted, performed so the data cannot be recovered.

A defined aspect used to measure data fitness, such as completeness, accuracy, timeliness, consistency, validity, or uniqueness, each with its own measurement rule.

A testable condition applied to data, such as a required field or a range check, whose pass or fail result can be monitored and reported over time.

Analyzing a dataset's actual values to reveal patterns, null rates, duplicates, and outliers, establishing a baseline before quality rules or remediation are set.

A recurring report that tracks quality measurements against targets by domain or dataset, making trends and accountability visible to governance bodies.

The core shared reference entities, such as customer, product, supplier, and location, that multiple systems rely on and that must stay consistent across the enterprise.

A controlled set of permitted values or codes (country codes, currency codes, status lists) used to classify or constrain other data consistently.

A register of reported data problems with owner, severity, status, and resolution notes, used to track remediation and spot recurring root causes.

A documented, time-bound approval allowing a defined group to deviate from a data policy or standard, with stated rationale, risk acceptance, and expiry.

A responsibility matrix that marks who is responsible, accountable, consulted, and informed for data activities, clarifying decision rights across roles and teams.

A hierarchical classification scheme that organizes data assets or concepts into nested categories, supporting consistent navigation, reporting, and policy scoping.

The governed handling of data through creation, storage, use, sharing, archiving, and disposal, with controls and owners defined at each stage.

Safeguards such as access rules, encryption, masking, and monitoring that enforce classification decisions and protect data from unauthorized use or loss.

Principles guiding responsible data use beyond legal minimums, including fairness, transparency, purpose limitation, and avoidance of foreseeable harm to people.

A structured evaluation of an organization's data practices against a capability model, producing a baseline and prioritized roadmap for governance improvement.

Any person or system that uses data for reporting, analytics, operations, or applications, whose needs and feedback shape stewardship priorities and definitions.

The governed process of granting approved users or systems access to a dataset, including request, approval by the owner, and periodic access review.