A Study on Visualization-Based Decision Support System Using Power BI

Abstract

The exponential growth of organizational data across industries has created an urgent need for effective tools that convert raw data into actionable intelligence. Decision Support Systems (DSS), traditionally reliant on static reporting and spreadsheet-based analysis, have undergone a fundamental transformation with the integration of interactive visualization platforms. This research paper investigates the deployment of Microsoft Power BI as a visualization-based Decision Support System (V-DSS) across organizations in the Marathwada region of Maharashtra, India, with a focus on how real-time dashboards, interactive data models, and AI-enhanced visual analytics enhance managerial decision-making quality, speed, and confidence. Employing a mixed-methods research design combining a structured survey of 135 managers, analysts, and business intelligence professionals with qualitative case study analysis of four organizations in Chhatrapati Sambhajinagar, the study documents significant improvements in decision-making cycle time (average 39% reduction), report generation time (average 67% reduction), and managerial confidence in data-driven decisions (from 51% to 84% among high Power BI adopters). Key Power BI capabilities driving these outcomes include the DAX (Data Analysis Expressions) formula engine, Power Query data transformation, natural language Q&A queries, and custom visual integration. The study introduces the Visualization-Decision Effectiveness Framework (VDEF) as a structured implementation model, while identifying critical barriers including data governance gaps, Power BI licensing costs, and organizational resistance to self-service analytics cultural change.

Introduction

The text discusses how organizations are increasingly dependent on large volumes of data and need effective Decision Support Systems (DSS) to convert this data into actionable insights. Traditional DSS tools like static reports and spreadsheets are no longer sufficient due to the complexity, volume, and speed of modern data. This has led to the rise of interactive visualization-based DSS (V-DSS), where users can explore and analyze data dynamically.

Microsoft Power BI is presented as a leading business intelligence platform that supports this shift through features like data connectivity, DAX calculations, AI-driven analytics, and interactive dashboards. Its adoption is growing in India, especially in industrial regions like Chhatrapati Sambhajinagar, where organizations are moving toward data-driven decision-making.

The literature review highlights key foundations of DSS theory, visualization design principles, cognitive decision support, and self-service analytics. It also shows that while BI tools like Power BI are widely adopted globally, many Indian Tier 2 organizations still face challenges such as limited data literacy, governance issues, and lack of digital maturity.

The study aims to evaluate Power BI’s effectiveness in improving decision-making speed, accuracy, and efficiency. It introduces the VDEF framework to assess and guide Power BI implementation. The research uses a mixed-method approach, combining surveys of professionals with case studies from organizations in Maharashtra.

Findings show that Power BI significantly improves decision-making by reducing report generation time, enhancing analytical capability, and increasing managerial confidence. Key features like Power Query, DAX, and interactive dashboards are especially valuable for integrating data and generating insights. However, successful adoption depends on factors like user skills, data quality, and organizational support.

Overall, the study concludes that Power BI-based visualization DSS plays a strong role in modern decision-making by enabling faster, more interactive, and more informed business analysis, especially in developing industrial regions.

Conclusion

This research provides compelling empirical evidence for the strategic value of Power BI as a visualization-based Decision Support System in modern Indian organizations. Across a sample of 135 analytical practitioners and four organizational case studies in Chhatrapati Sambhajinagar, the study documents significant and statistically robust improvements in decision-making cycle time (average 39% reduction), report generation efficiency (average 67% reduction), and managerial confidence in data-driven decisions (from 51% to 84% among high adopters) associated with structured Power BI V-DSS deployment. The Visualization-Decision Effectiveness Framework (VDEF) proposed in this research provides a structured, four-phase implementation model—Foundation and Data Readiness, Model Development and Dashboard Design, Deployment and Capability Building, and Optimise and Scale—designed to guide organizations through the technical and organizational dimensions of effective Power BI V-DSS implementation. VDEF addresses the critical prerequisite of data governance establishment, the analytical design standards required for dashboard effectiveness, the differentiated training requirements of diverse user cohorts, and the continuous improvement processes required to sustain and deepen V-DSS value over time. Critically, this study also surfaces significant implementation challenges—including data quality and governance deficits, licensing cost barriers for SME organizations, cultural resistance to self-service analytics, DAX skill gaps, and mobile connectivity limitations in industrial environments—that organizations must proactively address to realize Power BI\'s full V-DSS potential. For organizations in Tier 2 industrial cities such as Chhatrapati Sambhajinagar, where Power BI adoption is accelerating rapidly but implementation sophistication varies widely, this research provides empirically grounded guidance for evidence-based, effective, and sustainable visualization-based decision support development. As organizational data volumes continue to expand, and as the competitive premium on rapid, accurate, data-informed decision-making intensifies, visualization-based DSS platforms such as Power BI will become foundational capabilities for organizations across all sectors. The analytical investments, governance frameworks, and capability development approaches documented in this study provide a practical and evidence-based roadmap for organizations in Maharashtra and across India seeking to harness visualization technology for sustained decision support excellence.

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Copyright

Copyright © 2026 Sujata Suradkar, Prof. Pratik Dhanayat. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.