What Is a Data Strategy and Why It Matters in 2025

In 2025 we need to treat data as a strategic asset by using a data strategy to collect, manage, share, and use data effectively. As regulations tighten, expectations for ethical data use increase, and technologies like AI and data spaces reshape the playing field, data strategy becomes more essential than ever. But to be effective in 2025 and beyond, a data strategy must not exist in isolation—it must intersect meaningfully with data governance and data spaces to ensure compliance, collaboration, and resilience.

The Importance of a Robust Data Strategy

Data is now one of the most valuable assets for modern businesses, driving strategic decisions, customer insights, and operational efficiencies. A comprehensive, end-to-end data strategy enables companies to transform raw data into a competitive advantage, aligning with broader business goals.

An effective data strategy addresses common challenges such as disjointed efforts, overly technology-centric approaches, and misalignment with organizational objectives. It provides a holistic framework that integrates people, processes, and technology, ensuring data initiatives are aligned with business goals and can deliver impactful outcomes.

Why Do You Need a Data Strategy?

Without a clear data strategy, your organization is likely reacting rather than planning. You might be collecting too much irrelevant data, missing valuable signals, or exposing yourself to risk due to inconsistent practices.

A strong data strategy helps you:

• Align data initiatives with your business goals.
• Improve decision-making through trusted, well-governed data.
• Navigate compliance and data sovereignty requirements.
• Enable secure and interoperable data sharing through data spaces.
• Build systems that integrate with cross-border governance policies such as the EU Data Governance Act and ISO/IEC 19941.

Think of it as a compass that ensures your data efforts are headed in the right direction—especially when crossing borders, industries, or ecosystems.

Further Reading: AWS - What is Data Strategy?

What Questions Should a Data Strategy Answer?

Drawing from AWS and industry best practices, a strong data strategy should guide you through answering:

• What data do we have, and what data do we need?
• How do we ensure data quality, access, and interoperability?
• Who owns the data, and who governs it?
• How can we make data shareable while preserving sovereignty and trust?
• How does data support our current and future use cases—including AI, analytics, and regulatory compliance?
• How will we align with emerging data sharing protocols like the Eclipse Dataspace Protocol and maintain auditability per IDSA certification principles?

These answers help form a foundation not only for internal data operations but also for participating in trusted data ecosystems, like those enabled by data spaces.

Quote from the EU Data Strategy: Data should be accessible to all – businesses, researchers, governments – to innovate and deliver better services, while respecting privacy, security, and ethical standards.

The 5 Pillars of a Modern Data Strategy

A comprehensive data strategy should cover these five dimensions:

1. Data Collection and Ingestion

Focus on collecting the right data from reliable sources, both internal and external. A strategic approach here also considers sovereign data exchange, particularly when sourcing data from partners in regulated ecosystems. Leveraging principles from the EU Data Strategy ensures transparency, trust, and utility.

Read: European Data Strategy

2. Data Storage and Infrastructure

Ensure your infrastructure supports scale, security, and performance. This includes adopting architectures that can integrate with data spaces, such as those following the Eclipse Dataspace Connector (EDC) and IDSA principles. A flexible setup should also support data localization laws and jurisdictional compliance frameworks.

Refer to: ISO/IEC 19941:2017 on Cloud Interoperability

3. Data Governance and Control

This is where strategy meets execution. A solid governance layer enforces policies on access, usage, retention, and consent. It ensures you don’t just have data—but have trustworthy, compliant data. A data strategy without governance is just wishful thinking.

Add-on: Align with the EU Data Governance Act and frameworks like the IDSA Rulebook, which enforce accountability, interoperability, and usage control. Refer to IDSA Functional Requirements for specific implementation criteria.

4. Data Sharing and Collaboration

Modern data strategies should facilitate secure data exchange with partners, suppliers, and regulators. Here, data spaces provide a federated, policy-based infrastructure for data exchange. They make it possible to collaborate without giving up control.

Example: Think-it’s work on the GDSO Tire Data Space or the BMW supply chain emissions data use case shows how data strategy and data sharing can coexist securely through governance-backed infrastructures.

Refer to the EU Data Act (2023/2854) for legal foundations supporting B2B and B2G data access and reuse.

5. Data Activation and Value Creation

Data has no value until it’s used. A strategy must define how data supports AI, analytics, customer experiences, or regulatory reporting. Embedding context and metadata, facilitated by strong semantic models, allows systems and stakeholders to extract insights and act. Integration with tools like Langfuse or knowledge graphs can further support interpretability.

Data Spaces and Their Relation to a Company's Data Strategy

Data spaces are a form of data stewardship infrastructure that facilitate secure and controlled data sharing among different organizations within a data ecosystem. They emerged as an alternative to bilateral data sharing agreements, which can be restrictive and hinder innovation. By keeping data at its source and controlling access, data spaces address concerns related to data sovereignty and security.

Data spaces are particularly relevant to a company's data strategy as they provide a framework for data transactions based on a governance framework. This allows companies to retain control over their data while participating in broader data ecosystems, which can enhance innovation and collaboration. The European Strategy for Data aims to create a single European market for data, promoting sector-specific data spaces that encourage data sharing and collaboration.

Tying It All Together with Data Spaces

A data strategy grounded in today’s reality must support collaboration beyond the enterprise. This means building trust and compliance into your data architecture.

That’s exactly where data spaces come in. By providing a decentralized, sovereign, and governed environment for data exchange, data spaces help actualize your data strategy in the real world.

They enforce your rules, protect your rights, and enable data-driven innovation—without sacrificing control. And with IDSA and Gaia-X-aligned components such as the EDC Connector, your architecture can be both interoperable and certifiable.

Final Thoughts

Whether you’re optimizing supply chains, enabling AI, or navigating GDPR, the backbone of your efforts should be a smart, scalable, and collaborative data strategy.

It’s not just about better data—it’s about being ready for a future where data sharing, governance, and sovereignty are business-critical. And that future is already here.

Want to explore how Think-it helps companies implement data strategies within emerging data spaces? Get in touch with our team.

Frequently Asked Questions

What is the role of data governance in a data strategy?

Data governance provides a strategic framework that ensures data is managed, accessed, and used responsibly throughout its lifecycle, encompassing policies, processes, and roles necessary to maintain data integrity and security.

How do data spaces enhance a company's data strategy?

Data spaces facilitate secure and controlled data sharing among organizations, allowing companies to retain control over their data while participating in broader data ecosystems, enhancing innovation and collaboration.

Why is a robust data strategy important in 2025?

A robust data strategy is critical as data becomes one of the most valuable assets for businesses, driving strategic decisions, customer insights, and operational efficiencies.