Data transformation driven by business needs

We help organizations transform data from a technical resource into a strategic driver for business development. We achieve this by combining data-driven architecture, effective governance, and value-creating analytics.

Our approach

In a world where data is crucial for competitiveness, success is about more than just technology. It requires a strategic approach to collecting, managing, and using data across the organization—guided by a clear ethical framework that defines what you will and won’t use data and AI for.

Data is a strategic component of business strategy and a key to competitive advantage. That’s why a shared data strategy is essential. Governance today is about more than compliance - it functions as a digital accelerator, driving efficiency, innovation, and maximizing the value of technological investments.

Anne Hauberg Aakjer

Director, Immeo

We help you establish a clear and actionable data strategy that aligns business and IT, creating a reliable foundation for both operational efficiency and strategic innovation.

The strategy is developed:

In close alignment with your business strategy and ambitions
Based on your current state and opportunities
With prioritized transition plans
Using a thematic roadmap that continuously delivers measurable business value and strengthens your data foundation

Together, we develop clear data principles, effective processes, and a strong data foundation, making data a strategic asset. We strengthen your operating model and data culture with well-defined roles and targeted competency development to ensure both adoption and transformation.

Our key capabilities

Developing data strategies that ensure alignment across initiatives and connect directly to business objectives
Designing scalable data architectures that integrate data across sources and formats to meet both current and future needs
Implementing modern data platforms that ensure flexibility and high performance
Accelerating AI adoption through idea catalogs, focused AI initiatives, or hackathons that drive employee innovation

Implementing data governance frameworks that define active data ownership, established data principles, structured processes, and supporting tools
Strategic oversight and responsible data and AI utilization throughout their lifecycle
Data quality management and effective modeling of information and data structures

Standardization, integration, and consolidation of master data, including customer and product data
Improving data quality through structured initiatives and governance frameworks
Scalable data classification, management, and metadata democratization through modern data catalogs

Ensuring legal and best-practice compliance for data management
Facilitating effective collaboration between security, compliance, and audit functions
Implementing and managing key risk indicators with transparent reporting to senior leadership

From data to value

Data is only valuable when it is used to generate insights—especially insights that enable proactive decision-making.

Our approach ensures both strategic direction and practical implementation. We believe in a balanced approach that combines governance with innovation.

Through continuous collaboration with business, IT, and risk management, we ensure that data governance and utilization effectively support both compliance and business objectives.