Business Intelligence Tools in Organizations with a Focus on Power BI Applications in Civil Construction: A Systematic Literature Review

Read full text
Authors: Ornela Isbela Silva Zierz, Alberto Casado Lordsleem Junior
Cited by: 2
References: 136

Abstract

Business Intelligence (BI) comprises methods and technologies for collecting, organizing, and analyzing data to support managerial decision-making. This study presents a systematic literature review with a two-tier scope: first, identifying the most widely adopted BI tools across organizational contexts, and second, examining the specific application of Microsoft Power BI within the civil construction sector. The review followed the PRISMA guidelines and was complemented by the snowball sampling technique. A total of 81 articles published between 2015 and 2025 were analyzed to identify the most used tools, main application sectors, benefits, and challenges in BI adoption. The analysis combines descriptive bibliometric techniques with qualitative content analysis to examine publication trends, tools, application domains, and reported challenges. Results indicate that Power BI, Tableau, and Qlik Sense are the most frequent BI tools, with Power BI standing out for its integration with diverse data sources such as spreadsheets, databases, management software, and cloud platforms, enabling the creation of dashboards. The civil construction, business management, and manufacturing industries show the highest adoption rates, mainly for cost control, performance monitoring, and sustainability indicators. Reported benefits include operational efficiency, process automation, and improved decision-making. However, gaps remain regarding data standardization, interoperability, technological infrastructure, and user resistance. As a contribution, this review advances the existing literature by explicitly distinguishing general BI tool adoption from the sector-specific use of Power BI in civil construction, systematically classifying application domains and revealing limitations in maturity that remain underexplored in prior reviews.

Fields of Study & Subjects

Big Data and Business Intelligence Data Quality and Management BIM and Construction Integration

Publication details

Journal / source
Buildings
Publisher
MDPI AG
Volume
16
Issue
4
Pages
869–869
Publication date
22 February 2026
Language
EN