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Information derived from data describing the business activities in which organizations are engaged has become one of the most important resources for firms and for public organizations, as it indicates the breadth and the quality of their operations and orientates their visions, strategies and business activities. When firms and organizations can access relevant information pertaining to their clients, operations, rivals and business environment, or even organizing existing data to generate the needed information, they obtain crucial inputs and useful insights for decision making processes and for analyzing changes and trends in their business environment (Buchanan & O’Connell, 2006; Gibson et al., 2004).
As a part of their daily tasks, managers are required to make reliable and well-based decisions that adequately reflect the business reality or parts of it that are relevant to the business processes of the firm. These decisions are usually based on data that are augmented throughout the period of the operation of the firm. However, in many cases, these data amount to substantial volumes and are stored in different locations and forms that hinder their frequent retrieval and use, despite their substantial value and usefulness to decision makers (Markus, 2001). For example, the challenge that a large bank attempting to identify particular changes in the behavior of its customers from millions of daily transactions that they perform can be likened to finding specific information needles within a gigantic data haystack.
Business intelligence (BI) technologies were developed to address such challenges and to provide firms and other business entities with efficient and rapid solutions for the organization of their data (Philips & Vriens, 1999). Since the very first stages of their development, BI systems play a major role in decision making and in strategic thinking processes in a wide spectrum of organizations, re-organizing large volumes of unstructured data and enabling managers and decision makers to generate necessary information (and to some extent even to produce know-how).
Some scholars refer to BI as a tool (Graves, 2005), while others regard it in the broader context of a technology (Gibson et al., 2004; Hannula & Pirttimäki, 2003). Consequently, the definitions and the reference models of BI may vary and the impact of BI on the organization may be assessed in different ways. Despite the differences between the definitions of BI systems as products or as technologies, we can identify several commonalities among them. Researchers agree that the relative success of gathering data from the business environment of the firm and producing useful inputs for decision makers is amongst the most important assessment criteria of BI systems. Another common attribute of BI definitions consists of the links between organizations, systems and the domains in which they operate.
Prior studies on BI systems that attempted to produce a single and unified definition of BI systems (Bock et al., 2009; Buchanan & O’Connell, 2006) emphasized several essential objectives that BI systems aim to achieve, as follows (Codd, 1993; Corbitt, 2003):
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BI systems describe the business environment in which organizations operate, by producing specific indicators on the activities of actors within it.
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BI systems provide a description of the organizations themselves and their position in the market via the processed data and information.
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BI systems represent the links between firms, their customers, rivals and the economic climate in which they operate.
Following the models of Graves (2005) and Lönnqvist and Pirttimäki (2006), we can form a unified definition of BI systems as tools that gather, process, produce and present information on the business environment and on internal operations to provide useful inputs for managerial decision making processes within the firm.
In general, BI tools correspond to one or several of the following categories: