Privacy data mapping software that gives your records one living map to stand on

Privacy data mapping software inventories personal data and maps how it moves across systems, vendors, recipients, purposes, retention and transfers. In Acompli the map is built from reviewed records rather than a one-off workshop: systems, suppliers and processing context stay connected, so the map updates as the business changes instead of expiring in a diagram.

GDPR data mapping software keeps the accountability evidence behind your Article 30 register: which systems hold personal data, which vendors receive it, why it is processed, how long it is kept and where it crosses borders. Acompli feeds those facts straight into RoPA records and assessments without re-keying, with transfers flagged for Schrems II safeguards.

Each Article 30 record needs purposes, categories, recipients, transfers and retention - exactly what the data map holds. In Acompli the map is the feeder: processing activities link to the mapped systems and vendors behind them, so when the map changes, the affected register entries surface for review instead of silently going stale.

A DPIA starts with an accurate description of the processing - what data, which systems, which vendors, where it flows. Acompli pulls that description from the live map, so assessments begin from reviewed facts; and where a flow crosses borders, the transfer is flagged for Schrems II analysis inside the assessment.

No. The data map is the evidence layer - systems, flows and inventory; the RoPA is the legal register of processing activities under Article 30 that the DPC and ICO inspect. In Acompli they stay linked: the map feeds the register, and each register entry can show the mapped systems and vendors behind it.

The map should feed the Article 30 RoPA without re-keying, stay current as systems and vendors change, and make cross-border flows explicit. In Acompli the map is derived from reviewed records in the shared knowledge base, so it is not a parallel diagram that has to be maintained by hand.

There is no standalone 'data map' article, but Article 30 GDPR — applied in Ireland (enforced by the Data Protection Commission) and mirrored in the UK GDPR / Data Protection Act 2018 (enforced by the ICO) — requires controllers and processors to maintain accurate records of processing, and a data map is how those records stay accurate. A stale map yields a stale Article 30 record. Acompli derives the map from the same register that produces your RoPA, so the two cannot diverge.

It should surface every flow that leaves the EEA, the destination country, and the transfer mechanism (Standard Contractual Clauses, an adequacy decision, or a derogation), and link each to the Article 30 record and its Transfer Impact Assessment. Acompli groups recipients in third countries into explicit trust boundaries on the diagram, supporting GDPR Chapter V transfer governance with a regulator-ready visual. This operationalises the CJEU's Schrems II ruling (Case C-311/18), and it matters in Ireland in particular, where the DPC is lead supervisory authority for many large US-headquartered processors.

Because the map is derived from the records that already govern your estate — knowledge-base entities plus approved RoPA activities — so updates happen as part of normal review rather than a separate clean-up exercise. A deterministic engine owns the topology (what is on the map and how it connects); AI may only improve presentation and cannot invent, remove or rename nodes, so the diagram stays tied to the register.

No — mapping, the Article 30 RoPA, and DPIAs serve different purposes, and Acompli keeps them connected so you can move from a flow on the map to the right record, assessment or risk entry without re-keying. Each flow references the RoPA activity ID that produced it, and nodes carry provenance back to source records.

Mapping where personal data flows into AI and automated-decision systems lets a team check those systems against the EU AI Act's Annex III high-risk categories. When Acompli's Code Scan surfaces AI usage in a connected repository and a DPO confirms the findings, the confirmed entries are written into the data map alongside the records-driven nodes, so the AI footprint is visible. Classification against Annex III is a human decision; Code Scan produces reviewable signals, not determinations.

Yes. Existing system, vendor and location records can be imported into the shared knowledge base, and the map is generated from them — so you do not start from a blank diagram. Imported items remain reviewable, and the platform keeps enriching them as new assessments and records are approved.

The best data mapping software is decided less by how the diagram looks than by whether the map is derived from your Article 30 records rather than redrawn by hand, whether each flow shows its cross-border transfer mechanism, and whether every node traces back to a source record a DPC or ICO inspection can follow. Acompli's angle is to govern these as connected, human-approved records tied to the wider GDPR and EU AI Act programme, each traceable to approved evidence rather than a standalone diagram. For a balanced, unbiased comparison of the available suppliers - evidence-based, drawn from public sources, and honest about where competitors are stronger than Acompli - we have compiled capability charts and vendor-by-vendor breakdowns for you to consider in our full comparison library.