Executive Perspectives on Global Business Intelligence

2017 ◽  
pp. 13-22
Author(s):  
J. Mark Munoz
Keyword(s):  
Business Intelligence ◽  
Global Business

Implementing Business Intelligence in Contemporary Organizations

2015 ◽  
pp. 177-192 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Organizational Performance ◽  
Business Intelligence ◽  
Business Performance ◽  
Business Failure ◽  
Practical Implementation ◽  
Global Business ◽  
Business Decisions ◽  
Business Environments ◽  
Business Applications ◽  
Modern Business

This chapter introduces the implementation of Business Intelligence (BI), thus explaining the application overview of BI, the components of BI, the practical implementation of BI, the business value of BI, the trends in implementing BI, and the guidelines for implementing BI. BI is a broad category of business applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping business enterprise users make better business decisions. BI enlarges business performance, thus leading to higher level of efficiency, better quality outputs, better marketing decisions, and lessened risk of business failure in order to gain a competitive advantage in the global business environments. It is important to create and develop a BI system to enable the useful transformation of information into the valuable knowledge for enhancing BI in organizations. Implementing BI will increase organizational performance and achieve business goals in modern business.

The Role of Culture in Business Intelligence

2012 ◽  
pp. 38-51
Author(s):  
Jore Park ◽  
Wylci Fables ◽  
Kevin R. Parker ◽  
Philip S. Nitse
Keyword(s):  
Cultural Differences ◽  
Business Intelligence ◽  
Cultural Awareness ◽  
Information Gathering ◽  
Global Business ◽  
Foreign Markets ◽  
The Core ◽  
Core Components ◽  
Global Arena

Global business intelligence will struggle to live up to its potential if it fails to take into account, and accurately interpret, cultural differences. This paper supports this assertion by considering the concept of culture, explaining its importance in the business intelligence process, especially in foreign markets, and demonstrating that attention to culture is currently inadequate in most international business intelligence efforts. Without a tool capable of modeling social interaction in disparate cultures, BI efforts will under perform when extended to the global arena. The Cultural Simulation Modeler is examined as a means of enhancing essential cultural awareness. The core components of the modeler are explained, as are the limitations of automated information gathering and analysis systems.

Social Media Business Intelligence

2013 ◽  
Vol 5 (3) ◽  
pp. 51-73 ◽  
Author(s):  
David Bell ◽  
Sara Robaty Shirzad
Keyword(s):  
Social Media ◽  
Business Intelligence ◽  
Global Business ◽  
Market Participants ◽  
Domain Specific ◽  
Business Environments ◽  
Social Media Tools ◽  
Relationships Management ◽  
Business To Business ◽  
Social Media Network

Social media tools are increasingly used for relationships management among marketplace actors (e.g. organisations, suppliers and individuals). As markets become ever more global and dynamic, new entrants find themselves struggling to fully understand the marketplace, companies operating with it and changes that occur. The authors discuss Social Media Network (SMN) tools and outline a methodology and procedure that supports the identification of domain specific networks within particular global business-to-business environments. Research is carried out using SMN data about firms in the pharmaceutical industry. The authors use their own methodology to uncover market participants, linkages and prominent issues that may help new firms to position themselves effectively within a new marketplace. SMNs provide a sizable source of information and new approaches are required to fully leverage their considerable value. This paper explores how SMNs can be used as an effective source of business intelligence by utilising two popular SMN platforms.

scholarly journals Effectiveness of Agile Implementation Methods in Business Intelligence Projects from an End-user Perspective

10.28945/3515 ◽  
2016 ◽  
Vol 19 ◽  
pp. 161-172 ◽  
Author(s):  
Jerzy Andrzej Kisielnicki ◽  
Anna Maria Misiak
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
Traditional Approach ◽  
Added Value ◽  
Business Trend ◽  
End User ◽  
Global Business ◽  
Traditional Methods ◽  
User Perspective ◽  
Business Decisions

The global Business Intelligence (BI) market grew by 10% in 2013 according to the Gartner Report. Today organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics – Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However traditional methods are not efficient for changing business needs. The long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements in the end of the project. This article presents the latest market trends in BI systems implementation by comparing Agile with traditional methods. It presents a case study provided in a large telecommunications company (20K employees) and the results of a pilot research provided in the three large companies: telecommunications, digital, and insurance. Both studies prove that Agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach.

Implementing Business Intelligence in Contemporary Organizations

2016 ◽  
pp. 33-48
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Organizational Performance ◽  
Business Intelligence ◽  
Business Performance ◽  
Business Failure ◽  
Practical Implementation ◽  
Global Business ◽  
Business Decisions ◽  
Business Environments ◽  
Business Applications ◽  
Modern Business

This chapter introduces the implementation of Business Intelligence (BI), thus explaining the application overview of BI, the components of BI, the practical implementation of BI, the business value of BI, the trends in implementing BI, and the guidelines for implementing BI. BI is a broad category of business applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping business enterprise users make better business decisions. BI enlarges business performance, thus leading to higher level of efficiency, better quality outputs, better marketing decisions, and lessened risk of business failure in order to gain a competitive advantage in the global business environments. It is important to create and develop a BI system to enable the useful transformation of information into the valuable knowledge for enhancing BI in organizations. Implementing BI will increase organizational performance and achieve business goals in modern business.

Business Intelligence

2007 ◽  
pp. 14-34
Author(s):  
S. Maguire
Keyword(s):  
Competitive Advantage ◽  
Performance Management ◽  
Business Intelligence ◽  
Business Environment ◽  
Customer Relationship ◽  
Global Business ◽  
External Data ◽  
Effective Manner ◽  
Market Opportunities

The main aim of this chapter is to identify the important role of business intelligence in today’s global business environment and to reveal organizations’ understanding of business intelligence and how they plan to use it for gaining competitive advantage. Increases in business volatility and competitive pressures have led to organizations throughout the world facing unprecedented challenges to remain competitive and striving to achieve a position of competitive advantage. The importance of business intelligence (BI) to their continued success should not be underestimated. With BI, companies can quickly identify market opportunities and take advantage of them in a fast and effective manner. The aim of this chapter is to identify the important role of BI and to understand and describe its applications in areas such as corporate performance management, customer relationship management and supply chain management. The study was conducted in two companies that use BI in their daily operations. Data were collected through questionnaires, personal interviews, and observations. The study identified that external data sources are becoming increasingly important in the information equation as the external business environment can define an organization’s success or failure by their ability to effectively disseminate this plethora of potential intelligence.

scholarly journals Analysis of the Introduction of Business Intelligence and Data Warehousing into Businesses in Latvia

2021 ◽  
Author(s):  
Janis Birznieks ◽  
◽  
Lasma Licite-Kurbe ◽  
Keyword(s):  
Financial Reporting ◽  
Business Intelligence ◽  
New Technologies ◽  
Data Warehousing ◽  
Global Business ◽  
Business Decision ◽  
Intelligence System ◽  
New Information ◽  
Near Future ◽  
Data Culture

The market of global business intelligence technologies reached EUR 18.3 billion in 2017 and is expected to reach EUR 22.8 billion in the near future, as such technologies provide companies with a number of benefits: new information for business decision-making, real-time financial reporting and manual work automation. Nevertheless, many companies around the world do not achieve the desired results of applying business intelligence and data warehousing technologies. The research aims to develop scenarios for applying business intelligence and data warehousing tools in entrepreneurship in Latvia based on an examination of the tools. The research has found that the companies examined in the case study have introduced business intelligence along with data warehousing; however, there are differences in applying the business intelligence and the level of its advancement. Overall, a business intelligence system makes core and support operations and processes faster, as well as reduces costs and requires less human resources. However, problems were identified concerning a lack of motivation in employees to learn new technologies. The scenario analysis concluded that large companies should perform as many administrative and technological processes related to the mentioned technologies as possible themselves rather than outsource them, which allows them to save funds on the development of such technologies and improve the company’s data culture.

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