Towards the Use of both Financial and Non-financial Data for Decision Making: A Conceptual Framework for Federated Database Systems
David X. Zhu, Sijing Zong

Abstract
Most of the data sources in business and academia are financial data. Non-financial data are difficult to collect, integrate, and retrieve and are in most cases stored as separate and heterogeneous data sources that could not be readily used in financial analysis and research. However the recent development in finance research has put significant attention on the behavioral aspects of the participants of business and financial activities, which in turn requires the inclusion of the non-financial data that are related to such activities. One of the possible solutions is the federated database, which is a collection of distributed databases that are heterogeneous and autonomous in nature. This research extends previous works on federated database systems and proposes a conceptual framework for an FDBS (federated database system) that facilitates centralized control, as in a centralized database system, over distributed heterogeneous databases with the capabilities of autonomously discovering and retrieving data from dispersed internal and external database systems. A comparison of centralized, distributed, and federated database systems is also provided.

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