This thesis aims at further developing the process of data valuation by integrating both non-financial and financial approaches. For this purpose, a framework was developed to simplify and guide the data valuation process, ensuring that all relevant factors are considered. It emphasizes the importance of the specific event and purpose driving the data valuation, and it accounts for both non-financial and financial aspects that influence the data’s overall value.

The primary practical and scientific contribution of this thesis is the development of a comprehensive framework that integrates non-financial and financial valuation considerations. To demonstrate the framework's practical application, three relevant data valuation events are examined: data asset transfer, company liquidation, and financial reporting. These events were chosen for their relevance to real-world business challenges and their ability to highlight the various contextual factors, such as financial reporting standards and legal implications, that can affect data valuation.

The insights gained from applying these events to the developed framework offer new perspectives on data valuation, with the potential to influence and improve how organizations approach the valuation of their data assets in the future. By providing a structured, integrative approach, this thesis aims to help businesses navigate the complexities of data valuation, leading to more informed decision-making and better alignment between data's strategic importance and its financial valuation.