Empowering modern business intelligence (BI) tools for data-driven decision-making: Innovations with AI and analytics insights

In the existing environment characterized by information abundance, decision-making skills determine the organization’s competitive position preservation. BI encompasses several technologies that have evolved in the recent couple of decades, as follows: It t allows enterprises effectively translate large volumes of raw data into productive insights hence enhancing decision making. This article evaluates progress on the state of art on modern BI technological solutions that have transformed the way that businesses manage information for value creation. This focus is on AI, ML, predictive analytics and cloud computing that have revolutionized business intelligence. In this research, the outcomes obtained from using modern BI tools are discussed depending on the type of industry. In eligible health care, AI practicing forecasting models estimate the number of patients and resources; thus enhances the health care working system. This is whereby financial institutions find it useful to use real-time data analysis in order to detect such activities and prevent risks. The case examples given are emblematic for the fact that reliance on knowledge is growing and underline how BI technologies can enhance efficiency, reduce expenditure and thus improve general organizational performance. However, the above developments have been noted, the use of current BI tools has the following challenges. The issues regarding privacy and security of the data, the problems associated with the roll out of large technological infrastructures coupled with the scarcity of trained professional labor to gather, analyze and understand the data remain difficulties. Furthermore, it could also be stated that data quality and governance are the major drivers for BI system impact. This research continues to indicate areas of future research as far as BI tool compatibility with large data sets, improving data governance, and more within moral theory as it relates to AI-based decision making. That said let me make it clear that as all these innovations are gradually embraced by enterprises BI tools remain pivotal in charting the future direction of analytical decision making.

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Publication Details

Journal
Edelweiss Applied Science and Technology
Published
2024-12-21
DOI
https://doi.org/10.55214/25768484.v8i6.3800
Citations
4
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.11
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article

Empowering modern business intelligence (BI) tools for data-driven decision-making: Innovations with AI and analytics insights

Bhaskar Das, Md Jamil Hossain, Shohoni Mahabub
4 citations
Edelweiss Applied Science and Technology
Big Data and Business Intelligence
2.11
article

Empowering modern business intelligence (BI) tools for data-driven decision-making: Innovations with AI and analytics insights

Bhaskar Das, Md Jamil Hossain, Shohoni Mahabub
article en
4 citations

Abstract

In the existing environment characterized by information abundance, decision-making skills determine the organization’s competitive position preservation. BI encompasses several technologies that have evolved in the recent couple of decades, as follows: It t allows enterprises effectively translate large volumes of raw data into productive insights hence enhancing decision making. This article evaluates progress on the state of art on modern BI technological solutions that have transformed the way that businesses manage information for value creation. This focus is on AI, ML, predictive analytics and cloud computing that have revolutionized business intelligence. In this research, the outcomes obtained from using modern BI tools are discussed depending on the type of industry. In eligible health care, AI practicing forecasting models estimate the number of patients and resources; thus enhances the health care working system. This is whereby financial institutions find it useful to use real-time data analysis in order to detect such activities and prevent risks. The case examples given are emblematic for the fact that reliance on knowledge is growing and underline how BI technologies can enhance efficiency, reduce expenditure and thus improve general organizational performance. However, the above developments have been noted, the use of current BI tools has the following challenges. The issues regarding privacy and security of the data, the problems associated with the roll out of large technological infrastructures coupled with the scarcity of trained professional labor to gather, analyze and understand the data remain difficulties. Furthermore, it could also be stated that data quality and governance are the major drivers for BI system impact. This research continues to indicate areas of future research as far as BI tool compatibility with large data sets, improving data governance, and more within moral theory as it relates to AI-based decision making. That said let me make it clear that as all these innovations are gradually embraced by enterprises BI tools remain pivotal in charting the future direction of analytical decision making.

Edelweiss Applied Science and TechnologyVol. 8(6)
Trine University (US)
Openalex Percentile: Top 10%
Big Data and Business Intelligence
2.11
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