Data governance and GDPR for Baden organisations: controls that produce evidence

The question that exposes an analytics estate is simple: who could see this dataset last quarter? In most organisations the honest answer takes a week of investigation.

This page covers data governance and compliance for analytics estates in Baden: what the Federal Data Protection and Information Commissioner (FDPIC / EDÖB) expects under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023, which sector rules bite hardest given the local economy of energy generation and supply, industrial machinery and engineering, and software and technology, and how to implement controls in Microsoft Purview and Power BI that produce evidence rather than paperwork.

What the Federal Data Protection and Information Commissioner (FDPIC / EDÖB) expects of an analytics estate

Under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023, the obligations that touch analytics most directly are data minimisation, storage limitation, access control, and the ability to answer access and erasure requests. Analytics estates fail these quietly: a warehouse accumulates every column from every source because it was easier than deciding, retention defaults to forever, and permissions are granted to individuals who then change role.

• The revFADP brought Swiss law closer to the GDPR but not identical to it: records of processing, impact assessments and breach notification follow Swiss rules, and an EU-shaped compliance pack needs adapting rather than copying.
• FINMA outsourcing expectations require documented control over cloud providers, including the right to audit and a tested exit plan.
• Article 321 of the Criminal Code and sectoral secrecy duties restrict who may see client-identifying data, which has direct consequences for row-level security design.
• Cross-border transfer of client data out of Switzerland is a board-level question in financial services, not an IT decision.

None of this requires a governance department. Four things, none of which needs a department: a catalogue that gets used, a classification scheme that actually drives retention and labelling, access through groups rather than individuals, and evidence anyone can generate on request.

Sector rules that bite in Baden

Baden's economy means the governance conversation here is not generic. With power and energy technology engineering and industrial automation shaping the local client base, these are the obligations that come up in practice.

Energy generation and supply

Market reporting obligations and NIS2 critical-infrastructure duties apply, and consumption data is personal data for domestic customers. Half-hourly or sub-hourly interval data at national scale, settlement runs that are revised months later, and metering that is partly estimated.

The practical consequence for an analytics estate is that access design cannot be retrofitted. Row-level and object-level security have to reflect how authority is actually delegated in the organisation, and the design needs testing from a non-privileged account rather than assumed from documentation.

Software and technology

Product telemetry on identifiable users needs a lawful basis and consent handling, and SOC 2 or ISO 27001 evidence often covers the analytics estate. Typical systems in scope: billing and subscription platform, CRM, product event pipeline, support platform and finance system.

Industrial machinery and engineering

Export control and dual-use classification data should be modelled explicitly where machinery is shipped outside the EU and UK.

Who can see what, and how you prove it

This is the question that exposes an estate, and the fix is unglamorous. The difference is between an afternoon of investigation and a parameterised report. Individual grants accumulated over years require the first; groups that mirror your control model allow the second.

The sequence is always the same: extract the permissions that actually exist, design groups around how the organisation really delegates authority, migrate and remove the individual grants, then make the evidence self-service so your second line runs the report instead of raising a request. For a business in energy generation and supply, the groups normally need granularity by function and by entity or site.

Classification, labels and the export problem

Most estates lose control of data at the export button. The intent is almost always benign, which is precisely why policy alone does not stop it. Sensitivity labels applied in Power BI travel with the exported file, so encryption and access restrictions persist outside the platform, and export can be blocked entirely for specific labels or audiences.

The classification scheme has to align to the information security policy you already have rather than introduce a competing taxonomy, and retention has to be enforced against your actual obligation under the revised Federal Act on Data Protection (revFADP / revDSG), in force since September 2023 instead of kept forever by default. Every control is then verified from a non-privileged account, because the most common finding in a governance review is a restriction that was configured correctly and never actually tried.

Working with Swiss organisations: the practical constraints

• Swiss engagements are precise about scope and documentation, and tolerate fewer surprises than UK projects.
• Multilingual stakeholder groups are normal: German-speaking head office, French-speaking region, English-language group reporting.
• Expect strict supplier onboarding, including security questionnaires and in some cases background checks before any data access.

In Switzerland, professional secrecy duties and client expectation push data to stay in-country far more strongly than elsewhere in Europe, and FINMA outsourcing expectations require documented control over the provider including a tested exit plan. Those are board-level questions, not IT decisions.

A 90-day plan that produces evidence

1. Days 1 to 15: assessAccess extract versus policy, data map, classification gaps, retention reality. Output is a risk-ranked remediation plan, ordered by exposure rather than by ease.
2. Days 15 to 35: defineAn operating model that names who owns what, a classification scheme, retention rules tied to the actual obligation, and access standards. Agreed with legal and with the business, because a scheme they did not approve will not survive contact with them.
3. Days 35 to 70: implementPurview scanning and catalogue populated, labels published and applied, access rebuilt onto groups, lineage switched on, suppression implemented in measures.
4. Days 70 to 90: evidenceAccess evidence reporting, audit pack generation, steward training, and the first governance review run with your team rather than for them.

That sequence works because each stage produces something usable on its own. If the programme stops after the assessment, you still hold a risk-ranked plan an auditor would accept. Book a technical review if you want that assessment for a Baden organisation.

We work across Switzerland and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Lucerne, Winterthur, St. Gallen, Biel/Bienne, Yverdon-les-Bains and Rapperswil-Jona.

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