05.08.2026
The 10 most important questions about data strategy
Data are, or should be, the most important foundation for business decisions in every company. Whether in marketing, finance, product development or HR, solid figures and facts lead to better outcomes. To achieve this, however, data must also be structured and accessible. That is only possible with a well-designed data strategy. We have summarised the 10 most important questions on this topic for you.
Dr Jan Scharfenberg
Partner Information Security, Managing Director
1. Why does our company need a data strategy?
A data strategy creates clarity on how data can contribute specifically to achieving business objectives instead of merely launching “IT projects”. It brings together priorities, responsibilities and investments.
2. What specific added value does a data strategy create?
It increases data quality, enables AI use cases and more efficient processes, and reduces risks in areas such as compliance and security — measurably reflected in better decisions and less friction. Costs can be reduced, time can be saved through optimised processes, and revenue can be increased through new business models.
3. How long does it take to build a successful data strategy?
Developing the strategy typically takes a few months; implementation is a multi-year change process. What matters is a clear roadmap with milestones, rather than a “big bang” project.
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4. What is the difference between data strategy, data governance and data management?
Data strategy defines the direction and objectives. Data governance defines roles, rules and decision-making paths. Data management ensures operational implementation in day-to-day business.
5. How are data strategy, data protection, information security and AI use cases connected?
A good data strategy integrates legal and regulatory requirements from the outset and turns compliance into an enabler, not a showstopper, for data-driven business models.
6. What role do data protection officers, information security officers, AI officers and compliance officers play?
They contribute requirements and risks and should be involved in strategy development at an early stage, so that solutions are designed to be legally compliant, secure and audit-ready from the outset.
7. How does a data strategy fit into our existing IT and system landscape?
The data strategy sets guardrails, such as target architecture and principles, without pre-empting the technical implementation in detail. It provides orientation for later IT and platform decisions.
8. Why is a holistic approach important, and what does it mean in practice?
The business, technology and compliance perspectives are considered equally and together: What objectives are we pursuing, which data and capabilities do we need for them, and how do we remain legally compliant and aligned with security requirements? This enables risks to be identified and mitigated early, while also leveraging synergies.
9. Who is an in-house data strategy particularly relevant for?
It is particularly relevant for management, the Chief Data Officer, the Data Governance Officer, data owners and data stewards but also for functions such as data protection, information security, AI governance, legal and compliance, which define methodological requirements and monitor compliance with them.
10. Do you also support technical implementation?
Our focus is on strategic advisory: target vision, governance, roles, processes and roadmap. For technical implementation, we work with specialised partners where needed or involve existing service providers.
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How we support you with your data strategy:
Maturity Assessment
- Maturity assessment, including a Data Capability Map, and gap analysis in a workshop
- Derivation of measures and definition of milestones
- Creation of a roadmap
- Improvement of data quality, for example for AI, and removal of barriers to innovation
- Enablement of AI use cases
Governance
- Development of guidance documents and policies
- Definition of roles and responsibilities
- Stopping the diffusion of responsibility
- Training and awareness programmes
Regulatory Mapping
- Holistic assessment of the interfaces between the GDPR, the AI Act and the Data Act
- Establishment of an AI inventory based on the ROPA / VVT
- Conducting data protection impact assessments and fundamental rights impact assessments
- Leveraging synergies and implementing compliance requirements in a practical way
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