Data-driven business decision making: leveragingpredictive analytics and BI dashboards

In today’s world of Big Data, organizations are beginning to rely on data-driven decision-making (DDDM) and business intelligence (BI) to increase operational performance, improve strategic planning, and gain a competitive advantage with the help of predictive analytics and dashboards. This paper focuses on the fundamental role of DDDM in business through the use of cutting-edge analytics that make predictions about upcoming outcomes using traditional data integrated with data modelling, data mining, and machine learning. In addition, BI dashboards, such as BI tools, can be used to explore data from basic data sets to improve business decisions. This study also explores the DDDM and BI core concepts and identifies the research gaps and difficulties by applying the methodology of reviewing peer journals related to data-driven business decisions through the use of predictive analytics and BI dashboards from 2018 to 2025, where 50 journals were selected. This paper describes how predictive analytics and BI dashboards can be used for DDDM in the future. An overview article is read that explains the method and presents the results.

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Published
2025-01-01
DOI
https://doi.org/10.54646/sapars.2025.18
Primary Topic
Big Data and Business Intelligence
Type
article
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article

Data-driven business decision making: leveragingpredictive analytics and BI dashboards

Pydi Sai Adarsh Malla
Big Data and Business Intelligence
article

Data-driven business decision making: leveragingpredictive analytics and BI dashboards

Pydi Sai Adarsh Malla
article en

Abstract

In today’s world of Big Data, organizations are beginning to rely on data-driven decision-making (DDDM) and business intelligence (BI) to increase operational performance, improve strategic planning, and gain a competitive advantage with the help of predictive analytics and dashboards. This paper focuses on the fundamental role of DDDM in business through the use of cutting-edge analytics that make predictions about upcoming outcomes using traditional data integrated with data modelling, data mining, and machine learning. In addition, BI dashboards, such as BI tools, can be used to explore data from basic data sets to improve business decisions. This study also explores the DDDM and BI core concepts and identifies the research gaps and difficulties by applying the methodology of reviewing peer journals related to data-driven business decisions through the use of predictive analytics and BI dashboards from 2018 to 2025, where 50 journals were selected. This paper describes how predictive analytics and BI dashboards can be used for DDDM in the future. An overview article is read that explains the method and presents the results.

Vol. 1(4)
University of Memphis (US)
Openalex Percentile: Top 60%
Big Data and Business Intelligence
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