A Descriptive Literature Review and Classification of Business Intelligence and Big Data Research

Rashid, Ammar; Khurshid, Muhammad Mahboob

doi:10.1007/978-3-031-10461-9_59

Cited by 4 publications

(2 citation statements)

References 52 publications

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“…The goal of DSS was to provide managers with tools and techniques to make better decisions based on data analysis. Early DSS systems were limited by the lack of access to data and the limited processing capabilities of computers at the time (Rashid and Khurshid, 2022).…”

Section: Historical Backgroundmentioning

confidence: 99%

Impact Of Business Intelligence (Bi) On E-Hrm Practices Within Ngos In Jordan

2024

qas

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The current study aimed at examining the influence of business intelligence (Data management, Analytics, Business performance management, Information delivery) on E-HRM practices within NGOs in Jordan. Depending on quantitative approach, and utilizing and online questionnaire that was distributed on a convenient sample of ( 203) employees working within NGOs in Jordan. SPSS was used in order to screen, classify and analyze the primary data collected, results of study indicated that there was a strong relationship between independent variable (BI) and dependent variable (E-HRM) with a variance of 56.7% and accepted the main hypothesis arguing that "Business intelligence has a statistically positive influence on E-HRM practices from the perspective of HR managers within NGOs". In addition to that, among the sub-variables of study; results indicated that (Data management, Analytics, Business performance management, Information delivery) were influential in presenting better E-HRM practices with the highest influence for information delivery scoring a variance of 49.5% with a strong relationship with dependent variable (E-HRM). Study recommended computerizing human resource databases and making them available to all employees, and activating the use of electronic means and information technology to benefit from them in practicing business intelligence and building human resource management strategies. Further recommendations were presented in the study.

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Section: Historical Backgroundmentioning

confidence: 99%

Impact Of Business Intelligence (Bi) On E-Hrm Practices Within Ngos In Jordan

2024

qas

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“…One of the crucial problems associated with BI is data management; this is because proper data management and information storage may facilitate strategic data collecting [4]. The most important aspect is that many reports may analyze and produce accurate, quick, and Internetaccessible reports such as the capital of assets, inventory, financial statement, and other reports [2].…”

Section: Introductionmentioning

confidence: 99%

Business Intelligence Capabilities and Critical Success Factors in Public Sector Company of Malaysia

Rodzoan

Abubakar

Zeki

2022

JST

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The study's objective is to investigate the business intelligence (BI) capabilities of public sector organizations as well as the essential success variables associated with those skills. The research was carried out due to the fact that there has been a growth in the usage of BI, and a large number of the tools that are utilized in its operations are not reviewed, despite the fact that the influence of the user is considered to be one of the primary concerns associated with it. The study used a quantitative research method to look at Malaysian organizations and come up with some hypotheses to test the variables related to BI's capabilities in the public sector of an organization. There were good, reasonable samples of people who took part in the research. A questionnaire was used to get the information. When examined, the findings confirmed the correctness of every hypothesis made. Therefore, there is a connection between elements involving infrastructure, teams, data, top-level support, and user participation in data quality. The findings of this study helped determine whether or not there is a correlation between data quality and the speed with which business data is updated across geographies, the precision with which data is captured, the timeline with which it is processed and reported, and the ease with which key performance measures can be established at various operational levels within the company.

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