scholarly journals THE ROLE OF SAP BUSINESS OBJECT TO SUPPORT A BUSINESS INTELLIGENCE PERFORMANCE

2017 ◽  
Vol 14 (1) ◽  
Author(s):  
Eileen Fransisca Abadi ◽  
Aleksandar Terziev ◽  
Alexander Setiawan
Keyword(s):  
Business Intelligence ◽  
Business Object

scholarly journals Role of Business Intelligence in Banking Sector for Achieving Competitive Advantage- An Empirical Analysis

2021 ◽  
Vol 19 (1) ◽  
Keyword(s):  
Competitive Advantage ◽  
Business Intelligence ◽  
Quantitative Research ◽  
Banking Sector ◽  
Statistical Tests ◽  
Firm Strategy ◽  
Middle Level ◽  
Mediating Role ◽  
The Impact

With recent advancements in information technology, organizations’ capability to acquire and analyze data for efficient decision making has increased. Good strategies promote alignment among processes and technology in use, which may result in better firm performance. However, there has been little focus on how firm strategies and business intelligence (BI) systems might play their part in forming organizational information and getting a competitive edge. Therefore, the purpose of conducting this study is to investigate the impact of firm strategy on firm competitive advantage with mediating role of BI adoption and moderating role of BI capabilities. For this, a quantitative research methodology was used, and data was collected from 300 middle-level managers in Pakistan's telecom sector. Statistical tests such as descriptive statistics, correlation, reliability analysis, one-way ANOVA, confirmatory factor analysis, and mediation analysis through Hayes process were performed using SPSS and AMOS. The findings revealed a positive link between firm strategy and competitive advantage, with business intelligence adoption serving as a mediating factor. Business intelligence capabilities positively moderate the relationship between BI adoption and competitive advantage. Hence, all proposed hypotheses (H1, H2, and H3) were approved. The contribution and Limitation of the study are also discussed.

The Role of Data Mining for Business Intelligence in Knowledge Management

2015 ◽  
pp. 12-33 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Human Resources ◽  
Organizational Performance ◽  
Business Intelligence ◽  
Statistical Significance ◽  
Practical Applications ◽  
Business Goals ◽  
Emerging Trends

This chapter introduces the role of Data Mining (DM) for Business Intelligence (BI) in Knowledge Management (KM), thus explaining the concept of KM, BI, and DM; the relationships among KM, BI, and DM; the practical applications of KM, BI, and DM; and the emerging trends toward practical results in KM, BI, and DM. In order to solve existing BI problems, this chapter also describes practical applications of KM, BI, and DM (in the fields of marketing, business, manufacturing, and human resources) and the emerging trends in KM, BI, and DM (in terms of larger databases, high dimensionality, over-fitting, evaluation of statistical significance, change of data and knowledge, missing data, relationships among DM fields, understandability of patterns, integration of other DM systems, and users' knowledge and interaction). Applying DM for BI in the KM environments will enhance organizational performance and achieve business goals in the digital age.

Knowledge Management and Business Analytics

2019 ◽  
pp. 1-42
Author(s):  
Nirali Nikhilkumar Honest ◽  
Atul Patel
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Business Intelligence ◽  
Business Performance ◽  
Virtual Organization ◽  
Data Driven ◽  
Business Analytics ◽  
Broad Category ◽  
Business Operations

Knowledge management (KM) is a systematic way of managing the organization's assets for creating valuable knowledge that can be used across the organization to achieve the organization's success. A broad category of technologies that allows for gathering, storing, accessing, and analyzing data to help business users make better decisions, business intelligence (BI) allows analyzing business performance through data-driven insight. Business analytics applies different methods to gain insight about the business operations and make better fact-based decisions. Big data is data with a huge size. In the chapter, the authors have tried to emphasize the significance of knowledge management, business intelligence, business analytics, and big data to justify the role of them in the existence and development of an organization and handling big data for a virtual organization.

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.

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