Business intelligence

2. Literature reviews:

2.1 What is Business intelligence?

According to Kulkarni et al., (2007) Business intelligence system is a strategic information system that provides actionable information using a centralized data warehouse, which is taken from many sources, and then converted into meaningful information through BI analytical tools, leading to informed decisions. Business intelligence highlights analysis of large amount of data about the organization and its operations. The major goal of BI is to improve the correctness and the quality of the input to the decision process.

Elbashir et al. (2008) believes that providing timely, relevant and easy-to-use information and to increase the ability to analyse business information for the sake of improving decisions made by managers among a broad range of business activities is the main purpose of BI. The aim of such a systems is to support knowledge workers at different levels in organisations

Eppler (2006) commented that such systems mainly support analytical decision-making and are used in knowledge-intensive activities. These activities have three important characteristics: they are often non-routine and creative (unclear problem space with many decision options), their specifications cannot be predefined in detail, their outcome is uncertain and yet their success often brings innovations and improvements.

Marco (2002) contends a true enterprise-wide Knowledge Management solution cannot exist without a BI-based meta-data repository. In fact, a meta-data repository is the backbone of a KM solution. That is, the BI meta-data repository implements a technical solution that gathers, retains, analyses, and distributes business knowledge which leads to a competitive advantage in the market.

Turban et al. (2008) compared BI to earlier decision support systems, business intelligence systems are derived from the concept of managerial information systems and provide artificial intelligence techniques as well as powerful analytical techniques, such as predictive analytics, online analytical processing, data mining, dashboards and scorecards, alerts and notifications, querying and reporting and data visualisations.

Negash (2004) refers to business intelligence systems as systems that “combine data gathering, data storage and knowledge management with analytical tools to present complex internal and competitive information to planners and decision makers”. The above definitions share the same idea that these systems gives actionable information delivered at the right time, right position and in the right form to aid decision-making. The main purpose is to improve the quality of input data, in order to improve decision making.

2.1 Why to measure BI?

The measurement of business performance has long traditions in organizations. It is a practical managerial tool that can be applied in various situations and for different purposes. In the context of Business Intellegence, too, some authors have identified its measurement as a common view among researchers is that the measurement of BI is difficult to carry out (Gartz 2004; Hannula and Pirttimäki 2003; Simon 1998) and only few organizations have any mechanism in place to measure the value of CI (Marin and Poulter 2004). Thus, measurement is considered an important phase of BI but at the same time it is considered difficult to carry out in practice.

According to Lönnqvist and Pirttimäki (2006), there are two main purposes for measuring BI: the assessment of BI in order to prove that it is worth the effort and the measurement of BI activities in order to help manage a BI process.

3. Methodology:

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