Data Strategy foundation

Governance models, stewardship, quality metrics, and sharing agreements that stand up to audits

Ground your data strategy in accountable operating models, steward ownership, measurable data quality, resilient sharing agreements, and regulatory mappings across GDPR, the EU Data Act, TEFCA, and OMB evidence policies.

Use this fundamentals pack as a checklist when drafting charters, runbooks, KPIs, and agreements before launching data sharing or analytics initiatives that will face supervisory review.

Governance models

Choose the operating model that fits your risk posture and regulatory footprint, then codify it in charters and decision rights.

  • Centralised. A single data office owns policy, reference architectures, and approvals for cross-border transfers and data sharing. Works best for regulated industries needing uniform GDPR accountability (Article 5(2)) and Data Act fairness obligations.
  • Federated. Domain councils maintain autonomy but conform to baseline policies on consent, retention, and interoperability testing. Aligns with Data Governance Act transparency, TEFCA QHIN exchange obligations, and sector-specific retention statutes.
  • Hybrid. Strategic domains (PII, payments, clinical) stay centralised while analytics sandboxes and open data products operate under federated guardrails. Publish decision matrices so stewards know when approvals escalate to the CDO, DPO, or CIO.
  • Decision cadence. Issue monthly calendars covering DPIAs, transfer impact assessments, contract renewals, and interoperability drills. Include pre-read packs and escalation triggers for risky processing (e.g., new third-country recipients or API scope changes).

Stewardship and ownership

Translate legal and interoperability obligations into enforceable responsibilities before data leaves core systems.

Role clarity and controls

  • Stewards. Own data quality thresholds, approve schema changes, and sign off on DPIAs and TIAs for their domains. Maintain Article 30 records and TEFCA information blocking attestations.
  • Owners and custodians. Owners set policy and budget; custodians operate pipelines with access provisioning, encryption, and retention controls that satisfy ISO/IEC 27001 Annex A and HIPAA safeguards.
  • Consumers. Data users accept permissible-use statements tied to contract terms, DMA Article 5(2) consent boundaries, and sectoral rules such as 42 CFR Part 2 segmentation.
  • Escalations. Route unresolved risks (e.g., cross-border gaps, high-risk AI processing) to the CISO or DPO within published SLA windows, recording rationale for supervisory inquiries.

Interoperability readiness

  • API assurance. Maintain FHIR R4 endpoints and EU Data Act portability APIs with authentication, consent capture, and machine-readable exports; log fulfilment timelines for auditability.
  • Metadata and lineage. Enforce ISO/IEC 11179 metadata, lineage tracing, and provenance stamps so TEFCA participants, EU data space members, and auditors can validate sources and permissible use.
  • Change management. Require steward approval for schema or API version changes, with regression testing and backward-compatibility windows documented in release notes and customer communications.

Data quality metrics

Use evidence-driven KPIs to prove data fitness, satisfy supervisory expectations, and prioritise remediation.

Fitness and accuracy

  • Accuracy and validity. Measure accuracy error rates against authoritative sources and validity conformance to schema or code sets. Map thresholds to ISO 8000 and BCBS 239 expectations.
  • Completeness. Track mandatory field completion by domain (e.g., patient demographics, payment IDs) with stewardship ownership for gap closure.
  • Consistency. Monitor cross-system reconciliations and duplicate resolution; publish lineage views showing harmonisation rules.

Timeliness and reliability

  • Latency. Record ingestion and publication SLAs for TEFCA exchanges, EU Data Act portability exports, and Evidence Act inventories.
  • Uptime and error rates. Report API availability, retry rates, and mean time to recovery for FHIR endpoints and portability services.
  • Drift and change. Track schema drift, pipeline changes, and materialised view refresh failures; link remediation tickets to owners and due dates.

Governance evidence

  • Access and permissible use. Measure completion of quarterly access reviews, DLP rule hits, and approvals for secondary use, aligned to DMA consent boundaries and HIPAA minimum necessary.
  • Request fulfilment. Track completion times for portability, access, and deletion requests with SLA variance reporting for GDPR and Data Act Articles 4 and 5.
  • Audit readiness. Maintain evidence vaults (TIAs, DPIAs, contract exhibits, test logs) aligned to ISO/IEC 27001 Annex A and HITRUST CSF mappings to speed regulator responses.

Data sharing agreements

Document obligations clearly so partners, regulators, and auditors see how rights, security, and interoperability are enforced.

Core clauses

  • Scope and purpose. Specify lawful bases, permitted processing, and prohibited secondary use, reflecting DMA Article 5(2) consent expectations and Data Governance Act neutrality.
  • Security and access. Require encryption in transit and at rest, role-based access, and quarterly access reviews; cite ISO/IEC 27001 Annex A controls and HIPAA safeguards where applicable.
  • Data quality and support. Include service levels for completeness, accuracy, timeliness, and interoperability testing, with credits or corrective action plans when thresholds are missed.
  • Breach and incident handling. Align notification timelines to GDPR Articles 33/34, state breach laws, and TEFCA reporting duties; define joint investigation steps and evidence preservation.

Cross-border and interoperability

  • Transfer mechanisms. Reference SCCs, UK IDTA or Addendum, adequacy decisions, or Data Privacy Framework participation. Require up-to-date TIAs for new destinations or sub-processors.
  • Interoperability obligations. Mandate FHIR R4 support, machine-readable portability exports, and testing windows for API version changes. Capture evidence of successful exchanges and issue management.
  • Audit and transparency. Provide regulator audit cooperation rights, evidence vault access (DPIAs, TIAs, SOC 2, ISO certificates), and annual attestation updates.
  • Termination and deletion. Define deletion, return, and archival procedures with verification steps and timelines tied to contract end or withdrawal of consent.

Regulatory mappings to anchor your operating model

Keep milestones, documentation, and evidence aligned to the statutes and frameworks most likely to be audited.

Privacy and data protection

  • GDPR. Map accountability (Article 5(2)), records of processing (Article 30), DPIAs (Articles 35/36), breach response (Articles 33/34), and cross-border transfer governance (Chapter V) to owners and evidence repositories.
  • UK GDPR. Mirror Article 30 records, DPIAs, and UK Addendum or IDTA coverage for transfers, including data bridge reliance where applicable.
  • US health data. Apply HIPAA Security Rule safeguards, 42 CFR Part 2 segmentation, and emerging state health privacy laws for reproductive and sensitive data categories.

Data sharing and interoperability

  • EU Data Act. Prepare for application on 12 September 2025 by documenting portability APIs, trade-secret protection routines, and dispute resolution clauses.
  • EU Data Governance Act. Maintain neutrality, transparency, and logging for data intermediaries; keep public registers where required.
  • TEFCA. Track onboarding to a QHIN, adherence to information blocking rules, and FHIR R4 exchange testing with evidence of uptime and incident response.

Evidence and accountability

  • OMB M-24-04 (Evidence Act). Maintain data inventories, quality assessments, and access policies for federal evidence-building expectations and agency risk postures.
  • Security frameworks. Cross-map controls to ISO/IEC 27001 Annex A, SOC 2 criteria, and sector overlays such as HITRUST to streamline auditor requests.
  • Audit trails. Centralise logs for DPIAs, TIAs, consent changes, and API testing; retain artefacts with clear owners and retention periods to satisfy supervisory reviews.

Operational diagrams for data flows, retention, and consent enforcement

Use these reference diagrams to brief stewards, engineers, and counsel on how data moves, when it must be retained or deleted, and how consent signals gate downstream use.

Data flow map showing capture, vendor ingestion, processing zones, governed outputs, retention controls, and assurance signals linked with arrows.
Map end-to-end flows from capture through vendor ingestion, processing zones, governed outputs, retention controls, and assurance signals. Each node lists concrete controls—DPIA IDs, SCC/IDTA alignment, pseudonymised workspaces, and deletion hooks—so owners can trace lawful basis and cross-border evidence.
Retention decision tree flowing from dataset identification to statutory timers, contractual archives, and deletion or pseudonymisation actions.
Apply a deterministic retention tree: identify dataset purpose, cite statutory timers (finance, clinical, safety), evaluate contractual evidence needs, then route to system-enforced schedules, safeguarded archives, or deletion with key shredding. Each branch preserves DSAR fulfilment and legal-hold documentation.
Consent signal routing from CMP capture to a consent service that normalises strings and enforces them across APIs, data platforms, and audit evidence.
Keep consent signals enforceable: capture TCF 2.2 strings and in-product toggles, normalise them in a consent service with immutable receipts, and push enforcement to gateways, SDKs, and data platforms. Row-level filters, feature-store denials, and withdrawal-triggered retention hooks keep downstream use within granted purposes.

Use this with the Data Strategy guides

Pair the fundamentals with Zeph Tech guides on cross-border transfer governance, interoperability engineering, and compensation under the EU Data Act to keep implementation aligned with statutory expectations.

Open the cross-border governance guide Return to the Data Strategy pillar