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Data as a Resource: Properties, Implications, and Prescriptions

October 15, 1998 | Anany V. Levitin , Thomas C. Redman | Data, AI, & Machine Learning

Almost every activity in which the enterprise engages, from the most mundane operation to the most far-reaching decision, requires data. Yet data are rarely managed well: few enterprises know what data they have; people cannot access or use data; and data quality is often low. Furthermore, individuals and business units often hoard data, leading to political battles over ownership. To help enterprises manage data as a business resource, the authors survey the fundamental properties of data and explore the special challenges and opportunities involved in working with data.

"Data" consist of "data models," which are the organization's definitions of entities, their attributes, and the relationships among them, and "data values," which are the specific realizations of an attribute of the data model for particular entities. "Data records" are the physical manifestations of data stored in paper files, spreadsheets, and databases. Data have many distinctive qualities: for example, they are intangible; easy to copy, share, and transport; can be destroyed or lost inadvertently; are used for a variety of purposes; and are renewable.

These and other properties of data have management implications in five key areas: making arrangements to supply the needs of data users; ensuring that individuals can access data; protecting data security; improving and maintaining data quality; and employing data effectively in operations and strategy. The authors offer a set of prescriptions to help enterprises meet these challenges: institute data quality and data supplier management programs, hone data needs, identify and manage critical information chains, recognize the proper role of technology, develop and disseminate an inventory of data resources, specify the terms under which data can be shared, avoid futile political battles, delineate management accountabilities, and ensure that senior executives lead the data management program.

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