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Data Security & Risk Management:
How Do You Classify Sensitive Data?

Establish clear classification levels, label data at creation, and enforce handling rules across the lifecycle. Align with regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and standards like ISO 27001 and NIST.

Connect Every Touch Target Key Accounts

Classify sensitive data by (1) defining tiers (Public, Internal, Confidential, Restricted), (2) mapping impact to confidentiality, integrity, and availability (CIA), (3) labeling sources at creation and ingestion, and (4) enforcing controls (access, encryption, retention) based on the label. Review classifications during change events and on a set cadence.

Principles For Data Classification

Business-first tiers — Use four clear levels: Public, Internal, Confidential, Restricted.
Risk-based criteria — Rate impact to customers, legal exposure, and operations using CIA and likelihood.
Label at source — Apply labels automatically via data discovery and at creation in apps and forms.
Enforce by policy — Tie each label to access, encryption, sharing, retention, and backup requirements.
Automate detection — Use pattern matching for PII/PHI/PCI and AI-assisted classification with human review for edge cases.
Lifecycle coverage — Extend labels and controls to collection, storage, processing, sharing, and disposal.
Prove compliance — Maintain evidence: inventories, data flows, handling rules, and periodic audits.
Train every role — Simple handling guides and tooling built into daily workflows reduce mistakes.

The Sensitive Data Classification Playbook

A practical sequence to define tiers, label consistently, and automate enforcement.

Step-By-Step

  • Inventory data & flows — Build a system-of-record: sources, fields, processing, storage, and sharing.
  • Define tiers & criteria — Public, Internal, Confidential, Restricted with impact thresholds and examples.
  • Establish handling rules — Access, encryption, retention, data subject rights, and breach notification triggers by tier.
  • Label at creation — Mandate labels in forms, repositories, and pipelines; default to most restrictive when in doubt.
  • Automate discovery — Use DLP/classification tools to scan cloud, email, endpoints, and data lakes for PII/PHI/PCI.
  • Integrate with IAM — Enforce role-based access and just-in-time elevation using labels as policy inputs.
  • Protect in motion & at rest — TLS 1.2+ in transit, AES-256 at rest, tokenization or format-preserving encryption for high-risk fields.
  • Monitor & alert — Log access by label, set anomaly thresholds, and quarantine exfiltration attempts.
  • Review & attest — Quarterly spot checks, annual policy review, and control evidence for audits.
  • Retire & dispose — Time-bound retention with defensible deletion and certified destruction.

Classification Tiers: What They Mean And How To Handle Them

Tier Examples Access Protection Sharing Retention
Public Website content, published reports Open to all Integrity controls; backups Unrestricted Per business need
Internal Org charts, non-sensitive metrics Employees/contractors SSO + MFA; basic logging Internal systems only Policy-defined
Confidential Customer PII, contracts, pricing Least privilege; approvals AES-256 at rest; DLP; EDR Need-to-know; DPAs for vendors Limited; legal holds apply
Restricted PHI, payment data, secrets Tightly controlled; JIT access Tokenization; HSM KMS; segmentation Exception-only; encrypted transfer Minimal; purge on schedule

Client Snapshot: Labels That Drive Control

A fintech mapped data flows, standardized four-tier labels, and connected labels to IAM and DLP policies. Within one quarter, unauthorized access alerts dropped 47%, vendor scope was reduced by 29%, and audit prep time fell from six weeks to eight days.

Classification makes protection actionable: when every dataset carries a label, policies follow the data—across apps, vendors, and regions.

FAQ: Classifying Sensitive Data

Quick answers for security, privacy, and operations teams.

What counts as sensitive data?
Personally identifiable information (PII), protected health information (PHI), payment card data (PCI), credentials, geolocation, and any data governed by contracts or laws.
How many tiers should we use?
Four tiers (Public, Internal, Confidential, Restricted) balance clarity with control. Add sub-labels if needed (e.g., Legal Hold, Export Controlled).
Do labels slow teams down?
Not when built into tools. Use defaults, templates, and automation so classification is applied with minimal clicks.
How do we handle mixed datasets?
Classify by the highest-risk element. Segment fields (tokenize or mask) so teams can use non-sensitive columns freely.
How often do we review labels?
Quarterly spot checks, event-driven reviews after system or process changes, and annual policy updates aligned to regulations.

Make Classification Work Every Day

We help define tiers, automate discovery, and tie labels to controls across your stack.

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