Regulatory Compliance

Regulatory Compliance in CluedIn — Step-by-Step Implementation Guide

This guide shows how to implement a Regulatory Compliance program in CluedIn covering data discovery, classification, subject rights (DSAR/SAR), minimization, retention, lineage, and auditing. It’s designed to help you meet frameworks like GDPR, CCPA/CPRA, LGPD, and sector policies.

Outcomes

  • End-to-end visibility of where personal data lives, how it’s processed, and who can access it.
  • Automated classification, tagging, and policy enforcement (minimization, masking, retention).
  • Subject rights fulfillment (access/export/delete/restrict) with auditability.
  • Dashboards & alerts for continuous compliance posture monitoring.

Prerequisites

  • Source access to systems that store personal data (CRM, ERP, Support, Product, Marketing, Data Warehouse, File Stores).
  • RACI set so the implementation team has Accountable access to governed objects.
  • A dedicated VM/server for heavy jobs (discovery scans, toolkit exports/imports).

Reference Compliance Model

Core entities

  • Person (data subject), Customer, Employee, Prospect
  • Consent (purpose, lawful basis, status, timestamp)
  • ProcessingActivity (system/process, purpose, legal basis)
  • DataAsset (tables/files/collections with PII)
  • DSAR (request, identity proof, scope, due date, status)

Tags & Taxonomy (examples)

  • Sensitivity: PII, SensitivePII, Financial, Health, Minor
  • Purpose: Marketing, Support, Billing, Analytics
  • Residency/Transfer: EU, US, RestrictedTransfer
  • Policy state: RetentionDue, DoNotSell, DoNotContact, MaskInUI

Step 1 — Connect & Ingest Sources

Portal: Data Sources → Add Source
Connect systems that likely contain personal data (CRM, support/ticketing, auth/IdP, billing, web/app events, marketing automation, data lake/warehouse, shared file stores).

  • Start with read-only access where possible.
  • Capture source metadata (owner, region, DPO contact) as attributes.

Step 2 — Data Discovery Scan

Portal: Compliance → Discovery
Run automated scans to detect PII patterns (email, phone, national IDs, names, addresses).

  • Include unstructured stores (notes, PDFs, CSV drops) if available.
  • Tag assets with PII/SensitivePII and map them to ProcessingActivities.

Step 3 — Classification & Tagging Rules

Portal: Governance → Rules (Data Part Rules)
Create rules to consistently classify records/fields:

  • Pattern rules: detect emails, phones, tax IDs → tag PII.
  • Domain-specific rules: payroll/benefits → tag SensitivePII.
  • Source-based rules: marketing lists → tag Marketing.
  • Confidence scoring + tags: ClassifiedHigh/Medium/Low.

Tip: Keep names short and consistent (e.g., ContainsPII, DoNotSell).

Step 4 — Build the Person Graph

Portal: Entity Matching → Person/Customer/Employee
Link identities across systems to a single Person:

  • Blocking keys: (email), (phone), (name+dob), (customerId).
  • High-confidence rules: exact email/phone; Medium: fuzzy name + same domain/country.
  • Review candidates in Data Stewardship; enable Unmerge for errors.

This enables subject-centric compliance actions later.

Step 5 — Consent & Purpose Management

Portal: Entity Explorer / Rules
Model Consent with attributes (purpose, lawful basis, source, timestamp, expiry).

  • Rules to enforce consent:
    • If Consent(purpose=Marketing).status != granted → tag DoNotContact.
    • If DoNotSell (CPRA) → exclude from ad/export segments; tag DoNotSell.

Step 6 — Data Minimization & Masking

Portal: Governance → Rules (Golden Record & Data Part)

  • Masking rule examples:
    • Mask PAN/IBAN except last 4 for UI: set MaskInUI=true + store hashed surrogate.
    • Drop free-text PII from analytics exports: remove or redact fields.
  • Minimization:
    • For Analytics purpose, persist only hashed IDs; remove names/emails.

Step 7 — Retention Policies

Portal: Governance → Retention Policies

  • Define policies by entity/purpose (e.g., Billing data = 7 years, Marketing leads = 24 months inactivity).
  • Action: Archive first; promote to Delete after validation.
  • Add tags on approaching expiry: RetentionDue.

Step 8 — DSAR / SAR Workflow (Subject Rights)

Portal: Compliance → Requests (DSAR)

  1. Intake: Create a DSAR entity with requester identity proof and scope (access/export/delete/restrict).
  2. Locate: Use the Person graph to collect linked records across systems.
  3. Assemble: Generate export package (JSON/CSV/PDF) excluding masked internal notes.
  4. Delete/Restrict: Apply rules to remove or lock records (respect legal holds).
  5. Audit: Log timestamps, handler, and evidence.
  6. SLAs: Track due dates (e.g., GDPR 30 days); dashboard alerts for SLA breaches.

Step 9 — Data Lineage & Auditability

Portal: Entity Explorer → History and Dashboards

  • Ensure merges, overrides, masking, exports, and deletions are captured in History.
  • Maintain lineage from DataAsset → ProcessingActivity → Person.

Step 10 — Access Control & RACI

Portal: Governance → Permissions

  • Restrict SensitivePII fields; grant Accountable to stewards.
  • Create data-domain roles (DPO, Marketing, Support).
  • Enforce MaskInUI in views and exports.

Step 11 — Compliance Dashboards

Portal: Data Quality / Compliance Dashboards
Track:

  • % entities with PII classified
  • DSAR backlog & SLA compliance
  • Records by purpose & consent status
  • Retention due/overdue
  • Access/permission change logs
  • Cross-border transfer inventory

Step 12 — Publish/Integrate Controls

Portal: Exports

  • Marketing suppression list: export DoNotContact/DoNotSell.
  • Analytics feed: export minimized Person view (no direct identifiers).
  • Security tooling: send AccessAudit events to SIEM.
  • ERP/CRM: sync consent flags and masked fields.

Start read-only; validate mapping; then enable authoritative syncs.

Step 13 — Scheduling & Operations

  • Schedule discovery rescans, consent refresh, retention checks, DSAR jobs.
  • Run heavy scans off-peak on a dedicated server/VM to avoid timeouts.
  • Alert on anomalies (sudden surge in PII detection, SLA breach risk).

Step 14 — Validate, UAT & Promote

  • Test on 50–100 real subjects; verify consent enforcement, masking, and DSAR outputs.
  • Legal/DPO sign-off on survivorship, masking, and retention behaviors.
  • Package with Product Toolkit; ensure Accountable permissions; promote to staging → production.

Example Rules (Snippets)

Classify Email as PII

  • Condition: Email matches pattern
  • Action: add tag PII; set MaskInUI=true.

Enforce Do Not Contact

  • Condition: Consent(Marketing).status != granted OR tag DoNotSell
  • Action: add tag DoNotContact; exclude from Marketing exports.

Retention — Marketing Lead Inactivity 24m

  • Condition: LastActivity > 24 months ago AND Customer=false
  • Action: tag RetentionDue; after approval → Archive (then Delete).

DSAR — Restrict Processing

  • Condition: DSAR(type=Restrict).status = approved
  • Action: set ProcessingStatus=Restricted; mask identifiers in exports.

Go-Live Checklist

  • All high-risk DataAssets scanned and classified (PII, SensitivePII).
  • Person graph validated; false merges < 2%.
  • Consent model enforced; suppression feeds tested.
  • Masking/minimization rules verified in UI and exports.
  • Retention jobs scheduled; archive → delete flow validated.
  • DSAR workflow tested (access/export/delete/restrict) with audit artifacts.
  • Permissions/RACI applied; sensitive fields restricted.
  • Dashboards and alerts configured; SIEM integration (if applicable).
  • Promotion package built with Product Toolkit on a dedicated box.

Common Pitfalls & How to Avoid Them

  • Over-matching people by name only → require email/phone or multi-evidence.
  • Unscoped masking → accidentally remove needed analytics fields; prefer minimize over blanket delete.
  • Retention deletes re-ingested data → align ingestion filters with retention policies.
  • Consent not enforced downstream → wire suppression tags into every export and segment.
  • Running scans on laptops → use dedicated compute to avoid timeouts and throttling.

Success Metrics

  • ≥ 95% PII assets classified; 100% of sensitive stores inventoried.
  • DSAR SLA compliance ≥ 99%; end-to-end time ↓ month over month.
  • % of entities with valid consent for each purpose; suppression accuracy ≥ 99.5%.
  • Retention coverage (% entities under active policy) and overdue items = 0.
  • Reduction in access to sensitive fields (least-privilege trend).

Summary

By combining discovery, classification, consent enforcement, minimization/masking, retention, subject-rights workflows, lineage, and auditing, CluedIn gives you a repeatable, auditable framework for regulatory compliance. Start small, validate with real samples, and iterate rules until legal and operational stakeholders sign off.