Data, a core component of information systems, has long been recognized as a critical resource to firms. Data is the backbone of business processes; it enables efficient operations, supports managerial decision-making, and generates revenues as a commodity. This study identifies a significant gap between the technical and the business perspectives of data management. While functionality and technical efficiency are well addressed, the consideration of economic perspectives, such as value-contribution and profitability, is not evident. This study suggests that introducing economic perspectives can better inform the design and the administration of data management systems by accounting for the interplay between business benefits and implementation costs. To address the identified gap, the paper proposes a quantitative microeconomic framework for data management that links value and cost to the impartial/technological characteristics of data and the related information system. Such a mapping allows cost/benefit assessment and determination of optimal configuration of system and data characteristics to maximize value and profits. The framework is demonstrated through development of a model for tabular datasets, and the optimal design of dataset characteristics (such as time- span, desired quality-level, and the set of attributes to be included). The application of the model is illustrated using numerical examples.