Tailorable Technologies for Improving Business Intelligence Systems

Author(s):  
Shah J. Miah

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.

Author(s):  
Shah J. Miah

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.


Author(s):  
Shah J. Miah

The Australian farm-based businesses can be benefited from specially designed applications for cost-effective operation while maximizing profits to survive in economic and environmental crises. For decision support, existing business intelligence systems (BIS) approaches scarcely deal with specific user's provisions to adjust changing situations in decision making, without extra technical exertions. In this chapter, the authors describe a conceptual framework of tailorable BIS solution that is based on case study findings in that the highlighted requirements are relevant to address changing situations through enhancing end user's engagement. The activities of end user's engagement supported through the use of tailorable features that reinforce a shift from the traditional BIS process to a new provision where business owners can actively involve in adjusting their features to their decision support.


Author(s):  
Lapo Mola ◽  
Cecilia Rossignoli ◽  
Andrea Carugati ◽  
Antonio Giangreco

This exploratory study analyses the effects of the technical and organisational characteristics of business intelligence systems (BIS) on knowledge sharing, collaboration, and decision-making processes. The authors conducted a two-phase multi-method investigation. First, we surveyed 30 enterprises using BIS on a regular basis; then, we engaged in an in-depth case study with one of the respondent companies. Our results show that, on average, the technical and organisational characteristics of the BIS are positively associated with an increase in knowledge sharing, leading to an improvement in internal collaboration that subsequently brings improvement in the quality of decision-making. This case study adds that the way the BIS is designed and appropriated in organisations is important in obtaining such results is. A BIS being designed so that it can be appropriated by the general employee base is key in obtaining the desired organizational impacts. This suggests some requirements for BIS design that we will discuss in terms of theoretical and managerial implications.


2012 ◽  
Vol 3 (4) ◽  
pp. 14-53 ◽  
Author(s):  
Ana Azevedo ◽  
Manuel Filipe Santos

Since Lunh first used the term Business Intelligence (BI) in 1958, major transformations happened in the field of information systems and technologies, especially in the area of decision support systems. BI systems are widely used in organizations and their importance is recognized. These systems present themselves as essential parts of a complete knowledge of business and an irreplaceable tool in the support to decision making. The dissemination of data mining (DM) tools is increasing in the BI field, as well as the acknowledgment of the relevance of its usage in enterprise BI systems. BI tools are friendly, iterative, and interactive, allowing business users an easy access. The user can manipulate directly data, having the ability to extract all the value contained into that business data. Problems noted in the use of DM in the field of BI is related to the fact that DM models are complex in order to be directly manipulated by business users, not including BI tools. The nonexistence of BI tools allowing business users the direct manipulation of DM models was identified as the problem. More of these issues, possible solutions and conclusions are presented in this article.


2020 ◽  
Vol 8 (1) ◽  
pp. 272-280
Author(s):  
Hamed Fazlollahtabar ◽  
Minoo Talebi Ashoori

This paper concerns with an integrated business process to be applied as a decision support for market analysis and decision making. The proposed business intelligence and analytics system makes use of an extract, transform and load mechanism for data collection and purification. As a mathematical decision optimization, dynamic pricing is formulated based on customer entry-exit rates in a history-based pricing model. The optimal prices for products are obtained so that aggregated profit is maximized. A case study is reported to show the effectiveness of the approach. Also, analytical investigations on the impacts of the sensitive parameters of the pricing model are given.


2015 ◽  
Vol 11 (4) ◽  
pp. 1-25 ◽  
Author(s):  
Lapo Mola ◽  
Cecilia Rossignoli ◽  
Andrea Carugati ◽  
Antonio Giangreco

This exploratory study analyses the effects of the technical and organisational characteristics of business intelligence systems (BIS) on knowledge sharing, collaboration, and decision-making processes. The authors conducted a two-phase multi-method investigation. First, we surveyed 30 enterprises using BIS on a regular basis; then, we engaged in an in-depth case study with one of the respondent companies. Our results show that, on average, the technical and organisational characteristics of the BIS are positively associated with an increase in knowledge sharing, leading to an improvement in internal collaboration that subsequently brings improvement in the quality of decision-making. This case study adds that the way the BIS is designed and appropriated in organisations is important in obtaining such results is. A BIS being designed so that it can be appropriated by the general employee base is key in obtaining the desired organizational impacts. This suggests some requirements for BIS design that we will discuss in terms of theoretical and managerial implications.


2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.


2017 ◽  
Vol 9 (2) ◽  
Author(s):  
Sekar Sari Wiradarma ◽  
Ken Dhita Tania ◽  
Dinna Yunika Hardiyanti

AbstractBusiness Intelligence (BI) is a collection of theories, methodologies, processes, architectures, and technologies that convert raw data into quality information for business purposes. BI can handle a large amount of information that can help in identifying problems and developing new opportunities. In designing and implementing Business Intelligence (BI) concept for monitoring banking product service using reference business intelligence roadmap approach. Business intelligence roadmap is one example of BI development that can be emulated because of its agile and adaptive nature and is intended to support the development of BI. By utilizing Business Intelligence application on transaction history of banking product data, it is hoped able to produce information that can support in giving recommendation and decision making appropriately. The data and information generated also become more accessible and easier to understand (user friendly).Keywords: business intelligence, business intelligence roadmap, OLAP, banking products


Author(s):  
Aleš Popovič ◽  
Jurij Jaklič

The IS literature has long highlighted the positive impact of information provided by Business Intelligence Systems (BIS) on decision-making, particularly when organizations operate in highly competitive environments. The primary purpose of implementing BIS is to utilize diverse mechanisms to increase the levels of the two Information Quality (IQ) dimensions, namely information access quality and information content quality. While researchers have traditionally focused on assessing IQ criteria, they have largely ignored the mechanisms to boost IQ dimensions. Drawing on extant literature of BIS and IQ, the research sought to understand how, at its present level of development, BIS maturity affects IQ dimensions, as well as the role that business knowledge may exert in mobilizing this link. The authors test the hypotheses across 181 medium and large organizations. Interestingly, the data describe a more complex picture than might have been anticipated.


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