Delivering Internal Business Intelligence Services: How Different Strategies Allow Companies to Succeed by Failing Fast

2018 ◽  
pp. 157-176
Author(s):  
Rubén A. Mendoza
Keyword(s):  
Business Intelligence ◽  
Intelligence Services

Integrating Business Intelligence Services in the Cloud

2014 ◽  
pp. 686-700
Author(s):  
Volker Herwig ◽  
Kristof Friess
Keyword(s):  
User Interface ◽  
Business Intelligence ◽  
Software As A Service ◽  
Fully Integrated ◽  
Intelligence Services ◽  
Software Business ◽  
Cloud Applications

Business Intelligence (BI) solutions are among the popular applications that businesses demand in the Cloud. Although Business Intelligence functionality is already provided in the Cloud, vendors concentrate on providing existing products like Software as a Service, ignoring changing business and provisioning models of software. Business Intelligence functionality provided in the Cloud is lacking important integration features needed by other Cloud-based applications. While a simple upload of the data to be analyzed into a Cloud-based BI solution is already possible and well established, the visualization of the results and the interactive parts of the analysis are always provided inside the Cloud-based BI solution itself. However, as this chapter shows, common usage scenarios of integrated Cloud applications demand an integration of the analysis reports from BI applications into the user interface of other Cloud-based applications. This chapter describes how a fully integrated Cloud-based BI solution can collaborate with other Cloud-based applications. The technical concept illustrated with an example delineates how the required interface can be provided.

Towards Automation of Business Intelligence Services Using Hybrid Intelligent System Approach

2013 ◽  
Vol 4 (4) ◽  
pp. 61-92 ◽  
Author(s):  
Rajendra M. Sonar
Keyword(s):  
Business Intelligence ◽  
Ad Hoc ◽  
Intelligent System ◽  
Value Added ◽  
Case Based Reasoning ◽  
Intelligent Technique ◽  
Intelligence Services ◽  
Wide Range ◽  
Operational Systems ◽  
Human Decision

Business Intelligence (BI) includes many tools, techniques and technologies. BI processes often involve team of human decision makers and end-users to extract, explore and analyse the data. The results, decisions or models after analysis need to be implemented into operational systems. There can be considerable time delay between business events happening and action taken thus loosing opportunities. Intelligent techniques such as rule-based reasoning and case-based reasoning have been used extensively to address wide range of intelligent tasks including personalisation and recommendation. Some BI tasks can be modelled, automated and delivered through services rather than done on ad-hoc basis. The authors represent a service based approach to BI where a service corresponds to a well defined analytical functionality implemented using intelligent technique(s), filtering techniques or hybrids of them accessing only relevant data from database specifically modelled and designed for such tasks. The authors discuss an application of the approach for a value-added service in mobile domain.

An Exploratory Study of Infrastructure Barriers and the Role of Semantic Data Exchange Technologies in the Provisioning of Business Intelligence Services

2012 ◽  
Vol 3 (3) ◽  
pp. 45-59
Author(s):  
Rubén A. Mendoza
Keyword(s):  
Business Intelligence ◽  
Data Exchange ◽  
Business Processes ◽  
Technology Development ◽  
Semantic Data ◽  
Intelligence Services ◽  
The Status ◽  
Enterprise Level ◽  
It Executives

Business Intelligence (BI) has been a top technology development concern for high-ranking IT executives over the past decade. The objective of BI is to use data analysis as a competitive weapon, deeply integrated into business processes. The ability of an organization to provide enterprise-level BI services depends heavily on its IT strategy, itself a function of existing technology investment. Previous research has described four IT architecture stages ranging from isolated applications to modular services, each with increasing complexity and service capabilities. Representatives from four companies were interviewed about the status of their BI activities, and the resulting data helps identify common barriers faced by these organizations in the provisioning of enterprise-level BI services. Interview results also describe the success of a limited-scope operational BI system by one of these firms, and the role of semantic data exchange technologies, primarily XML, in this system.

Integrating Business Intelligence Services in the Cloud

2016 ◽  
pp. 572-585 ◽  
Author(s):  
Volker Herwig ◽  
Kristof Friess
Keyword(s):  
User Interface ◽  
Business Intelligence ◽  
Software As A Service ◽  
Fully Integrated ◽  
Intelligence Services ◽  
Software Business ◽  
Cloud Applications

Business Intelligence (BI) solutions are among the popular applications that businesses demand in the Cloud. Although Business Intelligence functionality is already provided in the Cloud, vendors concentrate on providing existing products like Software as a Service, ignoring changing business and provisioning models of software. Business Intelligence functionality provided in the Cloud is lacking important integration features needed by other Cloud-based applications. While a simple upload of the data to be analyzed into a Cloud-based BI solution is already possible and well established, the visualization of the results and the interactive parts of the analysis are always provided inside the Cloud-based BI solution itself. However, as this chapter shows, common usage scenarios of integrated Cloud applications demand an integration of the analysis reports from BI applications into the user interface of other Cloud-based applications. This chapter describes how a fully integrated Cloud-based BI solution can collaborate with other Cloud-based applications. The technical concept illustrated with an example delineates how the required interface can be provided.

The Effective Factors on User Acceptance in Mobile Business Intelligence

2014 ◽  
Vol 72 (4) ◽  
Author(s):  
Ghazal Bargshady ◽  
Katayoon Pourmahdi ◽  
Panteha Khodakarami ◽  
Touraj Khodadadi ◽  
Farab Alipanah
Keyword(s):  
Business Intelligence ◽  
Information Quality ◽  
User Acceptance ◽  
Mobile Service ◽  
System Quality ◽  
Mobile Business ◽  
Mobile Access ◽  
Intelligence Services ◽  
Desktop Computers ◽  
Current Article

Mobile business intelligence used for business intelligence mobile service applications increasingly. According to Gartner (2011), global smartphone sales had arrived at 630 million in 2012, and are supposed to reach 1,105 million items in 2015. As a result, business intelligence users not only rely on desktop computers, while they as well want mobile access to joint and used data. Nevertheless, few studies have been consummate on mobile business intelligence services and the user acceptance rate of mobile BI is still moderately low. For these reasons, the current article centred on the significant of the factors and levels of mobile business intelligence user acceptance that affect the mobile business intelligence user Acceptance. The conceptual model planned and data collected between mobile business intelligence users and quantitative method used. The collected data, analysed by SPSS software. The result of data analysis exposed that how factors such as organization climate, information quality, system quality, society effect and individual effect were influenced user acceptance in mobile business intelligence applications. 

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

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.

Od Business Intelligence do Business Performance Management

2012 ◽  
pp. 39-43
Author(s):  
Janusz Nesterak ◽  
Bernard Ziębicki
Keyword(s):  
Performance Management ◽  
Business Intelligence ◽  
Business Performance ◽  
Business Performance Management

Zarządzanie przedsiębiorstwem we współczesnych warunkach wymaga stosowania zaawansowanych systemów umożliwiających gromadzenie i przetwarzanie informacji do postaci użytecznej w podejmowaniu decyzji zarządczych. Możliwości takie stwarzają systemy klasy Business Intelligence. Systemy te obecnie są już szeroko stosowane w krajowych przedsiębiorstwach. Ostatnio coraz popularniejsze stają się systemy określane mianem Business Performance Management, które są traktowane jako kolejna generacja Business Intelligence. Istota systemów Business Performance Management dotychczas nie była szeroko prezentowane w literaturze krajowej. Część badaczy zajmujących się tą tematyką traktuje wymienione kategorie systemów jako tożsame. W artykule przedstawiono istotę systemów Business Performance Management oraz omówiono różnice pomiędzy tą kategorią rozwiązań i systemami Business Intelligence. Omówiono także elementy tworzące systemy Business Performance Management. Przedstawiono również metodykę oraz korzyści stosowania Business Performance Management w przedsiębiorstwach. (abstrakt oryginalny)

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