Business Intelligence Modeling: A Case Study of Disaster Management Organization in Pakistan

Author(s):  
Sohail Asghar ◽  
Simon Fong ◽  
Touqeer Hussain
2019 ◽  
Vol 10 (2) ◽  
pp. 36-56
Author(s):  
Mattias Strand ◽  
Anna Syberfeldt

Organizations are showing an increasing interest in incorporating external data into their business intelligence solutions. Such data allows for advanced analytics and enables more comprehensive and inclusive decision-making. However, external data incorporation is relatively unexplored in the literature, and scientifically published details on up-and-running BI solutions are very sparse. In addition, published literature concerning the incorporation of external data into BI solutions is often rather synoptic or rather old (originating from data warehouse related literature). Therefore, the authors present the results of an action case study at a public waste management organization, illustrating detailed aspects of external data incorporation related to the back-end of the solution such as data selection, source characteristics, acquisition technologies and frequencies, and integration approaches. Given that the external origin of the data poses specific problems that must be overcome in order to allow for successful incorporation initiatives, special attention was paid to such problems.


2021 ◽  
Vol 16 (4) ◽  
pp. 1042-1065
Author(s):  
Anne Gottfried ◽  
Caroline Hartmann ◽  
Donald Yates

The business intelligence (BI) market has grown at a tremendous rate in the past decade due to technological advancements, big data and the availability of open source content. Despite this growth, the use of open government data (OGD) as a source of information is very limited among the private sector due to a lack of knowledge as to its benefits. Scant evidence on the use of OGD by private organizations suggests that it can lead to the creation of innovative ideas as well as assist in making better informed decisions. Given the benefits but lack of use of OGD to generate business intelligence, we extend research in this area by exploring how OGD can be used to generate business intelligence for the identification of market opportunities and strategy formulation; an area of research that is still in its infancy. Using a two-industry case study approach (footwear and lumber), we use latent Dirichlet allocation (LDA) topic modeling to extract emerging topics in these two industries from OGD, and a data visualization tool (pyLDAVis) to visualize the topics in order to interpret and transform the data into business intelligence. Additionally, we perform an environmental scanning of the environment for the two industries to validate the usability of the information obtained. The results provide evidence that OGD can be a valuable source of information for generating business intelligence and demonstrate how topic modeling and visualization tools can assist organizations in extracting and analyzing information for the identification of market opportunities.


2014 ◽  
Vol 17 (2) ◽  
pp. 220-231
Author(s):  
Pamela Clavier ◽  
Hugo Lotriet ◽  
Johan Van Loggerenberg

High expectations are set for Business Intelligence (BI), yet it fails to consistently deliver accordingly: there are numerous reports of BI challenges and failures. Existing approaches to address BI challenges are largely found to be ineffective, highlighting the need for a new approach. This paper examines how BI is perceived or understood and establishes that, firstly, BI is inherently grounded in Goods-Dominant (G-D) logic and secondly, that this can be linked to the challenges that are experienced within BI. A recommendation is made for a shift to Service-Dominant (S-D) logic as a new avenue of exploration to assist in overcoming BI’s prevailing challenges. Identifying the inherent G-D logic in BI provides the first step necessary in making this shift. Research findings are based on an interpretive case study of a South African Banking institution as well as a literature review.


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