Systemtic Review Enhancing Business Intelligence through Data Science Integration in MIS Platforms

This study systematically reviews the integration of data science into Management Information Systems (MIS) and its implications for enhancing business intelligence (BI). By synthesizing findings from 56 peer-reviewed studies, the research highlights the transformative potential of data science in augmenting MIS functionalities through predictive analytics, real-time processing, and unstructured data analysis. Key challenges, including data privacy, ethical considerations, and technical barriers, are discussed, alongside emerging opportunities presented by cloud-based platforms and blockchain technologies. The study emphasizes the variability in integration effectiveness across industries, advocating for tailored, context-specific strategies. This review provides a comprehensive understanding of the evolving landscape of MIS and data science, offering insights for researchers and practitioners seeking to leverage advanced analytics for strategic decision-making.

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Publication Details

Journal
Strategic Data Management and Innovation
Published
2024-11-02
DOI
https://doi.org/10.71292/sdmi.v1i01.4
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
Controls
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article

Systemtic Review Enhancing Business Intelligence through Data Science Integration in MIS Platforms

1 citations
Strategic Data Management and Innovation
Big Data and Business Intelligence
0.53
article

Systemtic Review Enhancing Business Intelligence through Data Science Integration in MIS Platforms

article en
1 citations

Abstract

This study systematically reviews the integration of data science into Management Information Systems (MIS) and its implications for enhancing business intelligence (BI). By synthesizing findings from 56 peer-reviewed studies, the research highlights the transformative potential of data science in augmenting MIS functionalities through predictive analytics, real-time processing, and unstructured data analysis. Key challenges, including data privacy, ethical considerations, and technical barriers, are discussed, alongside emerging opportunities presented by cloud-based platforms and blockchain technologies. The study emphasizes the variability in integration effectiveness across industries, advocating for tailored, context-specific strategies. This review provides a comprehensive understanding of the evolving landscape of MIS and data science, offering insights for researchers and practitioners seeking to leverage advanced analytics for strategic decision-making.

Strategic Data Management and InnovationVol. 1(01)
Malaysia University of Science and Technology (MY)
Openalex Percentile: Top 22%
Big Data and Business Intelligence
0.53
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Systemtic Review Enhancing Business Intelligence through Data Science Integration in MIS Platforms · Strategic Data Management and Innovation (2024) | TGRS Research Map | TGRS