Data management encompasses all processes that ensure the collection, storage, protection, and utilization of an organization’s information. By 2026, this discipline is no longer limited to choosing a backup tool or a cloud server: it incorporates new regulatory constraints, particularly related to NIS2, DORA, and the AI Act, which require documenting every access and proving compliance during an audit.
Traceability of data access: a requirement that tools alone do not cover
Most content on data management focuses on quality, centralization, or management software. One angle remains absent: complete traceability of access and the ability to demonstrate, with evidence, who accessed or modified a piece of data, when, and from which application.
The convergence between NIS2, DORA, and the AI Act strengthens this requirement. According to Insight, compliance is no longer just about knowing where the data is hosted, but also about who can actually access it and how to demonstrate this during an audit. For a company, this means that simple encryption or regular backups are no longer sufficient: timestamped access logs, retained for a defined period, and usable by a third party are necessary.
The services offered by BackUpYourBrain specifically cover this type of support, articulating backup, security, and documentation of flows to meet compliance audit requirements.
In practical terms, a data management service that ignores this aspect exposes the company to legal risk, even if its backups are technically impeccable.
Backup and cloud storage: selection criteria beyond price
The natural reflex is to compare cloud backup offers based on the price per gigabyte. This approach overlooks several parameters that determine the actual reliability of a storage solution.
Location and data sovereignty
With the current European regulatory frameworks, the physical location of servers determines the applicable legal regime. Hosting outside the European Union complicates proving compliance during an inspection, even if the provider guarantees end-to-end encryption.
The Data Act, which is taking shape in France, adds another layer: companies must plan for access, portability, and sharing of data from the design stage of services. DLA Piper emphasizes that this obligation now also applies to data generated by connected objects (IoT), a scope that many backup solutions do not yet integrate.
Operational resilience and restoration
A backup service is judged as much on its restoration capability as on its storage reliability. Two technical criteria deserve special attention:
- The guaranteed restoration time: some cloud offers announce unlimited storage but do not commit to a specific timeframe for making data available again after an incident.
- The granularity of restoration: being able to recover a single file, a folder, or a complete system state at a given date radically changes the utility of the service in a crisis situation.
- The frequency of restoration tests: a provider that does not offer regular testing leaves the company to discover flaws at the worst possible moment.
Obligations of the AI Act regarding datasets
Since August 2, 2026, the AI Act imposes transparency obligations for certain artificial intelligence systems, particularly conversational systems and AI-generated content. This regulation directly concerns data management services.
For any company that uses or develops a tool incorporating AI, three obligations emerge:
- Document the datasets used to train or feed the system, including their origin and scope.
- Identify the AI systems subject to reporting or labeling obligations for content.
- Implement specific traceability mechanisms, distinct from those already provided for personal data protection.
A data management provider that does not integrate this regulatory dimension into its offering leaves its clients to manage an increasing risk of non-compliance on their own. Documentation of datasets becomes an expected deliverable, not a bonus.
Data governance: structure before tooling
Installing data management software without having defined roles, access rules, and validation circuits amounts to automating disorder. Data governance precedes technological choice.
Operational governance relies on three concrete pillars. The first is the clear assignment of responsibilities: who validates a structural change, who authorizes a new access, who supervises the deletion of obsolete data. The second is the definition of naming and classification rules, without which data becomes unfindable as volume increases.
The third pillar, often overlooked, is the periodic review of access rights. Organizations accumulate permissions over time with hiring and job changes. Without regular audits, inactive accounts retain sensitive access for months.
This structuring does not necessarily require an expensive tool. It requires an organizational decision made upfront and maintained over time. Infrastructure and security solutions then come in to apply these rules, not to invent them.
The European regulatory framework of 2026 makes this sequence non-optional. During a NIS2 or DORA audit, it is the documented proof of governance that is examined, not the technical sheet of the software used. A tool without documented governance protects neither the data nor the company.
