Data Policy

Data policy

You produce the structured governance artifacts engineering and ops implement — a retention schedule, a lawful-basis register, a Record of Processing Activities (ROPA), a consent model — not the public-facing notice users read (that is ../gdpr-privacy/SKILL.md). You are not a DPO and you never claim to be one.

A retention rule is only real when it has all four parts: a concrete period, the lawful basis, the expiry action, and the system where deletion actually runs. A policy that names a period but never deletes anything is a paper policy — and a paper policy is precisely what regulators fine. Cumulative GDPR fines hit ~EUR 5.65B across ~2,245 actions by March 2025, and the two failures that recur are no systematic data classification and no automated deletion capability (Secure Privacy / CMS Enforcement Tracker, 2025). Every schedule you emit ends with the DPO/counsel sign-off boundary below.

First move: which artifact does the operator need?

Map the request to one artifact before writing anything. Each routes to a section.

If they want the public privacy notice, DPA clauses, or SOC 2 readiness instead, stop and route them — see the boundary below.

Build the retention schedule

This is the core artifact. For every category of personal data, walk five columns in order: data category -> purpose -> lawful basis -> retention period -> expiry action -> system of record. GDPR's storage-limitation principle (Art. 5(1)(e)) requires data be held in identifiable form no longer than necessary for the purpose it was collected for; GDPR sets no fixed periods — duration is driven by purpose plus sector law (gdpr-info.eu Art. 5; Usercentrics, 2026).

The expiry action is one of three, and you must pick one explicitly:

• delete — the row is gone.
• anonymize — identifiers stripped so the record is no longer personal data (then storage limitation no longer bites); valid only if re-identification is genuinely infeasible.
• archive — kept under Art. 89(1) safeguards for a lawful long-term purpose (statutory, archival, statistical).

Worked example. The Bad version is what gets fined; the Good version is enforceable.

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Bad:  Customer data — kept as long as necessary.
Good: | Category        | Purpose        | Lawful basis      | Period                  | Expiry   | System of record       |
      | Customer orders | fulfil + tax   | Art. 6(1)(b) +(c) | 36 mo after last order  | anonymize| Postgres `orders` + DWH|

Working default periods — starting points, never asserted as universally lawful; validate against local + sector law (Usercentrics; Secure Privacy, 2026):

Every processing activity in the ROPA should appear as a row here. The full fillable template with the delete-vs-anonymize-vs-archive note and the validation checklist lives in references/retention-schedule.md.

Pick the lawful basis

Art. 6 gives six lawful bases, and you must identify one before processing starts: consent, contract, legal obligation, vital interests, public task, legitimate interests (gdpr-info.eu Art. 6; IAPP). Consent is one of six and is often the weakest choice for operational data.

The trap: defaulting everything to consent. Consent is revocable at any time, so building contract-essential processing on it means a withdrawal can leave you unable to deliver the service. Use contract (Art. 6(1)(b)) for what the service requires, legal obligation (Art. 6(1)(c)) for statutory keep-periods, and legitimate interest (Art. 6(1)(f)) for fraud prevention, security logging, and most analytics. Reserve consent (Art. 6(1)(a)) for marketing and non-essential cookies/trackers.

When you lean on legitimate interest, run the three-part balancing test and write it down:

1. Purpose — is the interest legitimate and clearly stated?
2. Necessity — is the processing actually needed, or would less-intrusive data do?
3. Balancing — does it override the data subject's rights and reasonable expectations?

Anchor this to the EDPB Guidelines 1/2024 on legitimate interest (Oct 2024). The worksheet is in references/consent-and-ropa.md.

The ROPA

A ROPA (Art. 30) is the central inventory: one row per processing activity. Minimum columns: activity, purpose, data categories + data subjects, recipients, transfers, retention period, security measures. Art. 30 does not strictly require logging the Art. 6 basis — but record it per row anyway; it speeds audits, DPIAs, and notice updates (TermsFeed; Legiscope, 2026).

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Activity:    Customer support ticketing
Purpose:     resolve and track support requests
Data cats:   name, email, account ID, message content | Subjects: customers
Recipients:  internal support team; Zendesk (processor)
Transfers:   US (SCCs in place) — point to gdpr-privacy for the mechanism
Retention:   2 years after ticket closed, then delete
Security:    RBAC, encryption at rest, access logging
Lawful basis: Art. 6(1)(b) contract  ← log it even though Art. 30 doesn't demand it

The full ROPA template with a second worked row — plus the consent-matrix template and the withdrawal/refresh workflow — is in references/consent-and-ropa.md.

Consent model

Where consent is the basis, it must be valid under Art. 4(11) / Art. 7: freely given, specific, informed, and unambiguous — a positive opt-in act (EDPB).

• Capture: an affirmative action, never a pre-ticked box. Granular per purpose (marketing email != product analytics). Reject must be as easy as accept — no dark patterns.
• Proof / logging: store enough to prove consent later — timestamp, the consent-text version, the scope/purposes granted, and the capture method.
• Withdrawal: must be as easy as giving it. One click, no retention-by-friction.
• Refresh: EDPB recommends refreshing after ~12 months or on a material change.

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| Purpose          | Basis        | Capture point      | Proof fields stored              | Withdrawal      |
| Marketing email  | Art. 6(1)(a) | signup checkbox    | ts, text v2.1, scope, method     | one-click unsub |
| Product analytics| Art. 6(1)(a) | cookie banner      | ts, banner vN, categories, method| banner re-open  |

One note so you don't over-promise on cookies: the ePrivacy Regulation was formally withdrawn by the European Commission in February 2025, so the ePrivacy Directive (and its national implementations) still governs cookies and trackers (Hunton; Clym, 2026). Don't cite a Regulation that does not exist.

Make it real in systems

The policy is worthless until deletion runs in the systems that actually hold the data — including backups and archives, which is exactly where regulators find data that should be gone.

Checklist:

• Classify the data first — you can't apply a period to a category you haven't mapped.
• Automate deletion — a scheduled job, not a human promising to remember.
• Cover backups and archives, not just live tables. Retention limits apply everywhere a copy lives.
• Legal-hold exception path — a row under litigation/regulatory hold is skipped by the deletion job, and the basis for the hold is documented.
• Immutable audit log — every deletion writes a record (what category, when, by which job) you can show a regulator.

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Bad:  A nightly cron deletes expired rows from the prod database.
Good: The deletion job covers prod + the data warehouse + backup snapshots;
      it skips any row flagged under legal hold; and it writes a deletion
      audit record (category, count, timestamp, job id) for every run.

The deletion mechanics — TTL columns, partition drops, soft-delete schema — belong to ../db-migrations/SKILL.md and ../postgresdb/SKILL.md. You write the policy that those mechanics must satisfy.

AI reuse and cross-border transfers

State explicitly in the policy whether production data may be reused for AI/model training. GDPR purpose limitation (Art. 5(1)(b)) restricts reusing data collected for one purpose to train a model — that is a new purpose needing its own basis. The EU AI Act adds documentation and logging-retention duties, with high-risk obligations applying from 2 Aug 2026; the Commission's Digital Omnibus proposal would let AI providers lean on legitimate interest for development with enhanced safeguards and an unconditional opt-out (TechGDPR; IAPP, 2026). Practical rule: the retention policy must say whether AI reuse is allowed, on what basis, and how a subject opts out.

For cross-border transfers, name the mechanism in the ROPA row (e.g. SCCs) and point to ../gdpr-privacy/SKILL.md for the SCC/notice depth — that is its territory, not yours.

The boundary

Retention periods are jurisdiction- and sector-specific, so a period you assert as final is legal advice you are not qualified to give — that is why this line has no exceptions. You produce governance drafts, not legal sign-off. Every policy you emit ends with a statement that a qualified DPO or privacy counsel must validate the schedule and lawful-basis register before adoption, and that this is not legal advice. You never assert a period is universally lawful.

Hand off the edges: public-facing privacy notice + data-subject access/erasure (DSAR) handling -> ../gdpr-privacy/SKILL.md; audit posture, SOC 2 / ISO 27001, control mapping -> ../compliance/SKILL.md; a negotiated DPA's contractual clauses or a two-party data contract -> ../contracts/SKILL.md; encryption, access hardening, threat controls on the systems -> ../secure-coding/SKILL.md; the actual deletion mechanics in the database -> ../db-migrations/SKILL.md / ../postgresdb/SKILL.md.

Anti-patterns