Abstract
Data valuation has been given increasing thought for the past 20 years. The importance of data as an asset in both the private and public sectors has systematically increased, and organizations are striving to treat it as such. However, this remains a challenge, as data is an intangible asset. Today, there is no standard to measure the value of data. Different approaches include market-based valuation, economic models, and applying dimensions to data. The first part of this article (Data Valuation Framework) examines these approaches and suggests a framework for grouping them. The second part of this article (Building and Scoring a Dimensional Data Valuation Model) describes how we built and scored a data valuation model.
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