Use Of Business Intelligence Tools Research Articles

Conceptualizing the Antecedents and Individual Impact of Business Intelligence in the Public Sector: The Technology-Organisation-Authoritative Framework

Business intelligence (BI) refers to a technological tool and process that transforms large and fragmented data into well-informed graphical insights to aid managerial decision-making. Recognizing the significant benefits of BI in leveraging extensive amounts of data, governments have been progressively investing in BI tools to improve efficiency in public offices. Nevertheless, despite a significant body of knowledge related to BI adoptions and their advantages, there is a dearth of theoretical understanding of how the effective use of the system affects employees' work performance, particularly among civil servants who have distinctive work natures compared to businesses. Most studies have also ignored external and institutional factors that influence individual usage, whilst studies on the effective use of BI tools remain limited. The paper thus proposed a new conceptual framework for examining the factors that influence the effective use of BI and its impact on individual job performance. The suggested propositions could provide a theoretical contribution by integrating technological, organizational and authoritative dimensions that are novel and unique to the public sector. It would also contribute to practical understandings for public managers and policymakers in ensuring the investment made on BI is worthwhile. Ultimately, the paper seeks to bridge the gap in BI studies related to public organizations.

Integrating business intelligence and predictive analytics in banking: A framework for optimizing financial decision-making

Integrating Business Intelligence (BI) and predictive analytics in banking has become a pivotal strategy for optimizing financial decision-making. This review paper explores this integration's theoretical foundations, current trends, and challenges while proposing a comprehensive framework to enhance decision-making processes. The proposed framework emphasizes the importance of a unified data architecture, advanced data integration techniques, and the synergistic use of BI tools and predictive models. By examining the implications for banking institutions, the paper highlights how this integration can transform strategic and operational decisions, improve risk management, and drive personalized customer engagement. Additionally, future trends such as the adoption of AI, real-time analytics, and enhanced data governance are discussed, along with recommendations for banks aiming to implement this integration successfully. The findings underscore the transformative potential of combining BI and predictive analytics to foster innovation, efficiency, and competitive advantage in the banking sector. Keywords: Business Intelligence (BI), Predictive Analytics, Banking Sector, Financial Decision-Making, Data Integration.

SSF-CDW: achieving scalable, secure, and fast OLAP query for encrypted cloud data warehouse

Implementing a cloud-based data warehouse to store sensitive or critical strategic data presents challenges primarily related to the security of the stored information and the exchange of OLAP queries between the cloud server and users. Although encryption is a viable solution for safeguarding outsourced data, applying it to OLAP queries involving multidimensional data, measures, and Multidimensional Expressions (MDX) operations on encrypted data poses difficulties. Existing searchable encryption solutions are inadequate for handling such complex queries, which complicates the use of business intelligence tools that rely on efficient and secure data processing and analysis.This paper proposes a new privacy-preserving cloud data warehouse scheme called SSF-CDW which facilitates a secure and scalable solution for an encrypted cloud data warehouse. Our SSF-CDW improves the OLAP queries accessible only to authorized users who can decrypt the query results with improved query performance compared to traditional OLAP tools. The approach involves utilizing symmetric encryption and Ciphertext Policy Attribute-Based Encryption (CP-ABE) to protect the privacy of the dimension and fact data modeled in Multidimensional OLAP (MOLAP). To support efficient OLAP query execution, we proposed a new data cube retrieval mechanism using a Redis schema which is an in-memory database. This technique dynamically compiles queries by disassembling them down into multiple levels and consolidates the results mapped to the corresponding encrypted data cube. The caching of dimensional and fact data associated with the encrypted cube is also implemented to improve the speed of frequently queried data. Experimental comparisons between our proposed indexed search strategy and other indexing schemes demonstrate that our approach surpasses alternative techniques in terms of search speed for both ad-hoc and repeated OLAP queries, all while preserving the privacy of the query results.

Enhancing strategic decision-making: The role of business intelligence tools and organizational ambidexterity

The study aims to investigate the influence of business intelligence on decision-making quality, considering organizational ambidexterity as a moderating factor. The sample included a broad group of professionals from the high-technology segment, surveying 450 respondents; 254 valid responses were obtained from senior executives, supervisors, and analysts. These respondents were selected as they had a clear ability for a deeper dive into strategic goals and international expansion strategies, effectiveness in capacities, and daily financial management improvement. The results showed that with the use of business intelligence tools, organizations were in a better position to provide a higher quality of strategic decision-making (p < 0.01) as it helped in the functioning of new opportunities to identify and capitalize, while keeping an eye on the current capabilities. The study underscores that organizational ambidexterity is one of the most dominant causes (p < 0.01) for the effective realization of the benefits of business intelligence. Thus, for effective decision-making, it is crucial for organizations to synergize business intelligence tools with their ambidextrous capabilities. This underscores the significant role of organizational ambidexterity as a moderator and further demonstrates its importance in optimizing the use of business intelligence to improve strategic decision-making processes.

Transforming Primary Healthcare Services with Centralized Health Intelligence: A Case Study from Qatar

Centralized Health Intelligence (CHI) represents an ecosystem where data, technology, and expertise converge to elevate the standards of healthcare services. In this case study, we explore the pivotal role of CHI in reshaping the healthcare paradigm at the Primary Health Care Corporation (PHCC) in Qatar. Adopting clinical information systems led to a wealth of data, necessitating the transformation of the conventional health information management team into the Business and Health Intelligence (BHI) Department. The establishment of a centralized enterprise data warehouse (EDW) and the use of business intelligence tools by the BHI Department further contributed to improved data governance. A meticulous Centralized Health Intelligence Framework was devised to ensure the effective use of PHCC's data assets. This framework encompasses policies and procedures related to data stewardship, information needs assessment, data classification, data privacy, and data literacy requirements. Through this study, we demonstrate how PHCC has harnessed CHI to redefine healthcare delivery by providing relevant stakeholders with easy access to advanced data analytics and data-driven decision-making tools. Implementing CHI infrastructure presents many challenges, including financial, technical, and organizational hurdles. Despite these challenges, CHI significantly benefits relevant stakeholders by providing enhanced access to health data, fostering active engagement. However, addressing data comprehension, security, and privacy concerns remains critical.

THE IMPACT OF BUSINESS INTELLIGENCE SYSTEMS ON PROJECT MANAGEMENT IN HIGHER EDUCATION: AN EMPIRICAL STUDY

The successful completion of projects depends on effective project management, particularly in the complex and dynamic environment of higher education institutions. Business intelligence (BI) tools can assist identify problems and hazards, facilitate decision-making, and offer insightful information on how projects are performing. The purpose of this study is to examine how BI systems are used for project management in higher education institutions and to suggest a successful project management strategy that incorporates BI systems. To determine the present state-of-the-art in project management and BI systems in higher education, the research technique includes a rigorous literature review of academic and industry sources. An analysis of a case study from a university that has used a BI system for project management is also included in the Study. The study's conclusions imply that BI systems can enhance project management at higher education institutions by supplying precise real-time data on project performance, risks, and problems. By facilitating better decision-making, early issue detection, and prompt problem resolution, the deployment of a BI system has improved project management, according to the case study analysis. The study suggests a successful project management strategy that incorporates BI systems in higher education institutions based on the findings. The following steps make up the suggested strategy: Project objectives and scope definition, project planning, BI system implementation, BI system performance monitoring, project issue and risk identification and mitigation, and continuous improvement are the steps in a project. The suggested framework can assist institutes of higher learning in managing projects successfully by making use of BI tools. The paper also outlines the critical success criteria for BI system deployment in project management in higher education institutions, such as top management support, transparent communication, user training, and efficient data governance.

ТЕНДЕНЦІЇ ВИКОРИСТАННЯ «ВЕЛИКИХ ДАНИХ» В БІЗНЕС-АНАЛІТИЦІ ПІДПРИЄМСТВ В УКРАЇНІ

The article is devoted to the study of the current state of «big data» analysis by enterprises and key trends in the field of business intelligence. Object of study – the use of «big data» in economic analysis. Purpose – to investigate the current state of «big data» analysis by enterprises and trends in the field of business intelligence. Methods of research – analysis, synthesis, generalization, systematization, graphic. The article examines statistics of the domestic enterprises' analysis of «big data» by sources of «big data» and by methods and techniques of analysis with a breakdown by type of economic activity and number 398 of employees. There is given an overview of the market of analytics and business intelligence platforms to work with «big data», their opportunities, advantages and disadvantages are analyzed. Key trends in the field of data and analytics for the near future are identified. It is established that the main problems in the development of the direction of «big data» processing in economic analysis in Ukraine are organizational and financial difficulties, lack of qualified personnel and lack of proper experience. A significant barrier to the use of business intelligence tools is the lack of practice of accumulating «big data» and the low quality of these data in domestic companies. These factors will significantly contribute to the further growth of the market of outsourcing services for business analysis of «big data». In the current conditions, it is expedient to introduce a single state operator of «big data», as they include personal data of citizens, which requires appropriate regulation and control. KEYWORDS: BUSINESS ANALYTICS, BIG DATA, ECONOMIC ANALYSIS, PLATFORMS OF ANALYTICS AND BUSINESS ANALYSIS, ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AUGMENTED ANALYTICS, CLOUD ANALYTICS

БІЗНЕС-АНАЛІТИКА ТА ЗАСОБИ ВІЗУАЛІЗАЦІЇ ДАНИХ

The article considers topical issues of business intelligence and data visualization, their impact on effective management decisions in modern companies. The aim of the article is to study the theoretical and methodological foundations of the use of visual content for making the most effective management decisions, systematization of the most popular business intelligence tools for visualization of marketing data. The main tasks of the business analyst and the most popular analytical resources on the Internet are defined in the work. It is noted that the use of business intelligence tools helps marketers to access relevant information, visualize statistics, conduct marketing research, model risks and take timely measures to prevent them. It is determined that data visualization has become one of the most important tools of business analytics, and the use of visual content allows you to convey the essence of the message concisely and conduct a quick analysis of data with the right emphasis. The classification of visualization according to the type of result (statistical, dynamic and interactive) is given. The main stages of business analyst work are analyzed in the work, the connection between information technologies and business analytics is investigated. The most popular analytical resources on the Internet are listed, the Google Analytics web analytics tool is analyzed, and its advantages and disadvantages are identified. It is noted that the data obtained from the use of only one tool analyst can be erroneous, so you need to compare indicators using information from different sources. The factors influencing the effectiveness of visual content in social networks are indicated. The modern market of data visualization tools is analyzed. The scientific novelty of the work is reflected in the definition of the most common tools for visualizing business intelligence data. It is concluded that with the constant growth of information in all spheres of life, there is a need to use automated systems to support management and innovation decisions, especially the growing demand for software for business analysis and visualization of data.

Use of the BI systems for organizing the information space of the university

This article is devoted to the method of constructing information-analytical systems of the university. For implementation, the author proposes to use business analytics systems. The article provides a comparative analysis of the use of business intelligence tools for business and university. A comparative table of the capabilities of existing business intelligence systems is also presented. The most optimal system for building the information-analytical system of the university has been proposed. We developed a model of the analytical report. Also in the article is an example of an interactive form of data analysis. The article is oriented on heads of higher educational institutions, as well as on companies developing data analysis systems and providing marketing services.

CONTROLLING THE CHANGING OF MANAGEMENT ACCOUNTING PRACTICES IN THE ENTERPRISE RESOURCES PLANNING ENVIRONMENT

The aims of this research is to give empirical evidence of changes in management accounting practices (MA) by examining the effects of changes in data quality, information quality and management accounting tasks on the efficiency and effectiveness of accounting, and indirectly on change in management accounting after the adoption of an enterprise resource planning (ERP) systems. Empirical analysis of the study used primary data from a survey of 29 manufacturing companies with 102 CFO respondents, accounting managers and business controllers, with a response rate of 28.43%, providing significant support for the proposed model. Structural equation modeling (SEM) approach with testing tools using partial least square (PLS) is used in this research. The linear thing with the results of previous research is the same, it was found that the erp implementation time is the determinant of significant MA changes, while the difference from previous researchers is in the end user, where the company that has adopted the ERP system has just felt a greater MA change when compared to users early on. The results showed that the implementation of global ERP and the use of business intelligence tools (BI) were significantly related to changes in MA practices.

Online corporate reputation: A panel data approach and a reputation index proposal applied to the banking sector

Managing an online corporate reputation (OCR) is increasingly strategic to improving the corporation’s economic performance. What becomes crucial is to collect, process and analyse the comments expressed in the online medium, considering them as an intangible asset with an impact on tangible assets and consequences on business value. This research contributes to show the potential of the big-data environment, enhanced by the use of business intelligence tools and combined with panel econometric models. This is complemented by the elaboration of an Online Corporate Reputation Index (OCRI) to measure the economic corporate performance. The findings show that after applying the conceptual model to the banking sector, the experience associated with ethics is the intangible asset that has the most impact on the economic performance associated with each bank. In addition, the definition of an index helps to position one company in relation to another and to an entire economic sector.

The importance of using a business intelligence tool for decision making

We seek to point out the importance, the main expectations and positive points in the use of a Business Intelligence (BI) tool for decision making, so that it can become a competitive advantage for the organization. Its main methodologies were bibliographic research, quantitative research and the case study of a fictitious company, as resources for collecting information, questionnaires were used in Google Forms, with quantitative analyzes of the data collected. As a result, we have the confirmation of the importance of using a Business Intelligence tool for operational growth, because the veracity of this data is fundamental for the construction of scenarios that can help during decision making and boost competitiveness, adding knowledge about the market to the company, it was concluded that data processing and the use of BI tools are extremely important for decision making, because in this way managers have assertive data in their hands and in an agile way gaining a competitive advantage in relation to organizations that do not use a BI tool.

Business Intelligence for Human Capital Management

This article presents the results of an exploratory study of the use of business intelligence (BI) tools to help to make decisions about human resources management in Portuguese organizations. The purpose of this article is to analyze the effective use of BI tools in integrating reports, analytics, dashboards, and metrics, which impacts on the decision making the process of human resource managers. The methodology approach was quantitative based on the results of a survey to 43 human resource managers and technicians. The data analysis technique was correlation coefficient and regression analysis performed by IBM SPSS software. It was also applied qualitative analysis based on a focus group to identify the impacts of business intelligence on the human resources strategies of Portuguese companies. The findings of this study are that: business intelligence is positively associated with HRM decision-making, and business intelligence will significantly predict HRM decision making. The research also examines the process of the information gathered with BI tools from the human resources information system on the decisions of the human resources managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structured as follows: a literature review concerning the use of the business intelligence concept and tools and the link between BI and human resources management, methodology, and the main findings and conclusions.

The potential of business intelligence tools for expert finding

Finding the right experts for data gathering through interview serves as a key for particular research works. However, most expert finding methods in the literature require great deals of technical knowledge, making them somewhat impracticable for business researchers without deep technical knowledge. Accordingly, there is a need for an expert finding solution for researchers without a deep technical background. As business researchers may have knowledge about business intelligence and its tools, the use of business intelligence tools can be used to solve such issue. The present paper discusses the process of using business intelligence tools to find potential experts for example topics. Subsequently, based on a literature review, criteria are presented for distinguishing different experts. Finally, the analytic hierarchy process is discussed for assigning weights to both selection criteria and potential experts. The audience of this paper is researchers who are familiar with business intelligence tools or would like to learn how to work with them

Inhibitors of business intelligence use by managers in public institutions in a developing country: The case of a South African municipality

Background: Business intelligence tools play an important role for businesses across all industries for their data and information management solutions. By harnessing the capabilities of business intelligence, companies are able to predict and better meet customer needs. This study investigates factors that inhibit managers’ use of business intelligence tools in a public organisation in South Africa, where there has been evidence of a very low uptake of business intelligence tools. Objective: The objective of this study was to establish factors that inhibit the use of business intelligence and data analytics tools by managers in public organisations. Organisations are likely to lose their competitive advantage and experience a negative impact on efficiency and service delivery if managers do not make use of analytics in strategic decision-making. Methods: The study utilised both qualitative and quantitative data. Qualitative data were collected from managers through interviews, whilst questionnaires and daily login recordings were used to collect quantitative data. Quantitative data were analysed using statistical methods, whilst qualitative data were analysed by thematic analysis. Results: The research revealed a wide range of factors that inhibit the use of business intelligence tools by managers. These factors range from personal, system quality, organisational, macro-environmental, behavioural beliefs and attitudes, effort perceptions and social influence to facilitating conditions. Conclusion: The article provides a comprehensive contextual situation regarding poor use of business intelligence and analytics tools in a large metropolitan public entity. The findings from the organisation under study would be deemed to apply to similar organisations throughout the country.

Understanding the Business Value Creation Process for Business Intelligence Tools in the UAE

Background: In today’s dynamically changing business environment, organizations are constantly striving to improve their organizational performance, and the use of business intelligence (BI) aids in this process. This is a key reason why BI has captured the attention of many academicians and practitioners. Most of the research on BI highlights its importance and the ways in which it facilitates decision-making; however, there is limited research on how the use of BI tools and applications benefits the organization by enabling it to convert the millions of dollars spent on BI investment into business value. This study validates the “business value of BI” framework by evaluating the business value creation process for BI tools in the UAE.

How the use of business intelligence tools in the fistula sector can improve surgical performance

Aims: The aim of Operation Fistula’s ongoing work is to incentivize our partnering clinical teams by providing performance-based funding. We do this using a coordinated chain of business intelligence tools, and by sharing detailed customized visual dashboards so they can track both patient outcomes and surgical performance. We have repurposed a number of leading business intelligence tools to create a patient tracking and performance management system. This platform combines several technologies to collect, store, and analyze data, which we communicate with our partners.
 Methods: In order for data to be collected into our system, our partner surgeons and nurses input patient data directly into customized, standardized, electronic forms on a tablet or phone. Results are uploaded in real time, and feed into the data visualization software. Our London-based team is then able to create data visualization dashboards, based on the collected data, which are shared with stakeholders in our partnering countries.
 Results: We are tracking surgical outcomes using our mobile data collection and visualization programmes. We are also measuring the impact of the digital performance-based funding model, currently being used in the SAVA region in Madagascar. Our partnering clinical teams have responded positively to the introduction of our system, which we have found to ensure quality standards of care.
 Conclusions: The initial phase of this work has yielded positive results. We have seen increased engagement and motivation from our partnering clinical staff, which exemplifies how both a performance-based funding system, and access to digestible data, can improve surgical performance.

The Use of Business Intelligence Tools to Analyze the Influence of Interactivity and Interaction Factors on the Assessment of Distance Students’ Performance in Virtual Learning Environments

This paper aims to improve the practice of distance education, by providing managers with a view of aspects that influence the progression of students. To that end, it analyses “Interactivity and Interaction” factors in Virtual Learning Environments (VLE) communication systems, seeking to understand how these elements influence the performance of distance learning students at the beginner level. The study was carried out using data from a Brazilian distance learning private university, which utilizes a virtual learning environment. The research involved four steps: construction of a business intelligence environment, statistical analytical work, decision trees and clustering techniques to describe data, establish the most relevant variables and identify standards that may support the conclusion. https://doi.org/10.26803/ijlter.17.9.6

A research on the use of business intelligence for academic research

PurposeAt the moment, business intelligence (BI) is known as the way for analyzing data in an organization. Simple search in the literature shows that there are many papers which discuss about BI applications and related matters. In addition, there are different approaches and tools that support using BI in organizations. This paper aims to focus on the use of BI tools for academic applications, and it describes how the academic area will benefit from using BI.Design/methodology/approachThis paper is based on using BI tools and other library studies.FindingsA process for using BI tools in academic applications has been presented. Also, two cases are stated about activities of e-learning participants and literature analysis, for which BI tools are used to analyze data and simplify difficult tasks.Originality/valueThis paper shows how BI tools can be used for research and academic applications.

User perspectives on business intelligence

The research articles in this issue are related to business intelligence in one way or another. The article by Salmas, Alebpour and Homayounvala is entitled “Identification and classification of organizational level competencies for BI success”. In their research the authors have identified competencies that can be used as a measure to evaluate an organization’s status with regards to business intelligence success. Since the study done by Adamala and Cidrin (2011) this journal has shown a strong interest in user evaluations of business intelligence systems. The article by Ghasemi and Rowshan presents a new approach to the early warning literature. Entrepreneurs are the group that more than anyone else are seeking out early insights and also rewarded by their ability to look ahead. In the literature this is known as “entrepreneurial alertness.” Science can never accept that some people are simply born entrepreneurs or have “eureka” moments: we want to understand why and how. From an intelligence perspective picking up early signals can be seen as a signal for which entrepreneurs to follow and listen to. The ability to gather data from socialmedia through the use of BI tools should make this possible once these entrepreneurs are identified. The article by Ghasemi and Rowshan does not go in this direction, but such research would be welcome in the future.The article by Avner entitled “Study on competitive intelligence in Isreal: 2016 update” is a status report for competitive intelligence within Israeli firms. The results are compared with a study conducted by the same author in 2006. The study shows that there has been no significant change in CI practices in Israel during the past ten years. It also confirms that competitive intelligence is primarily a tool used by larger organizations. This means that Israeli companies have been slower to adopt new business intelligence software, and this is something that respondents see as a problem.The article by Solberg Søilen entitled “Users’ perception of data as a service (DaaS)” is an investigation into a new market related to business intelligence. On one hand this is a survey addressing one particular type of users—namely market intelligence (MI), competitive intelligence (CI) and businessintelligence (BI) professionals and experts—and their preferences. On the other hand, this is a critical analysis about the consequences of the issues addressed by users. It is also an attempt to present DaaS in a shorter historical perspective.The case study on Qoros automotive manufacturing by Ahmadinia and Karim is an analysis of how the company could enter the European market. It has now been more than a year since JISIB decided to publish case studies as articles. The Qorors case is not only a good teaching case, but is also a goodillustration of how intelligence topics can be tied to marketing questions and the larger question about competitive advantage.As always, we would above all like to thank the authors for their contributions to this issue of JISIB. Since the beginning of the year the journal has been supported by a three year grant from the Swedish Research Council (VR). This has allowed us to increase the quality in layout design and review theEnglish grammar.