The use of multiple data sources for enterprise-level planning and decision making has become increasingly important. Information sharing among organizations can help achieve important public benefits such as increased productivity, improved policy-making, and integrated public services. This paper reviews uses of multiple data sources for enterprise-level planning and decision making. It identifies current research and practical experience in the use of multiple data sources to support performance measurement, strategic planning, and interorganizational business processes. The information was derived from journal articles and Internet sources. A series of cases are examined, and the benefits, issues, methods, and results of efforts that involve the integration of different data sources in the same organization and across multiple organizations are identified and compared. The purpose of this paper is to take the first steps towards the development of a methodology for integrating multiple data sources.
Data integration is the process of the standardization of data definitions and data structures by using a common conceptual schema across a collection of data sources. Integrated data will be consistent and logically compatible in different systems or databases, and can use across time and users. The scope of data integration is the extent to which that the standardization is used across multiple organizations or sub-units of the same organization.
This paper identifies and compares the issues, methods, and results of efforts that involve integrating different data sources 1) within one organization, and 2) across multiple organizations. Section 2) is subdivided into cases (I) where the different organizations are in the same sector of the economy (e.g. in business or government), and (II) where the organizations cross sectors (e.g. business and government).
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