The widespread use of business intelligence products, services, and applications piques the interest of researchers in this field. The interest of researchers in business intelligence increases the number of studies significantly. Identifying domain-specific research patterns and trends is thus a significant research problem. This study employs a topic modeling approach to analyze domain-specific articles in order to identify research patterns and trends in the business intelligence field over the last 20 years. As a result, 36 topics were discovered that reflect the field’s research landscape and trends. Topics such as “Organizational Capability”, “AI Applications”, “Data Mining”, “Big Data Analytics”, and “Visualization” have recently gained popularity. A systematic taxonomic map was also created, revealing the research background and BI perspectives based on the topics. This study may be useful to researchers and practitioners interested in learning about the most recent developments in the field. Topics generated by topic modeling can also be used to identify gaps in current research or potential future research directions.

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Business Intelligence Strategies, Best Practices, and Latest Trends: Analysis of Scientometric Data from 2003 to 2023 Using Machine Learning

The State-of-the-Art of Business Intelligence and Data Mining in the Context of Grid and Utility Computing: A PRISMA Systematic Review

En las organizaciones, la inteligencia de negocios es una herramienta tecnológica por excelencia para el análisis y procesamiento de datos históricos internos explotados a favor de la organización, generando información oportuna y confiable. Nuestro objetivo fue identificar cuáles son las metodologías para la implantación de soluciones de inteligencia de negocios basadas en data warehouse, así como la adaptabilidad de las mismas a los diferentes tipos de empresas. Para ello realizamos una revisión del estado del arte de artículos publicados en revistas indexadas en base de datos bibliográficas como: Web Of Science, Scopus, ScienceDirect, SciELO a través de Google Scholar con el propósito de tener una selección de información de calidad que nos proporcionen aportes importantes para esta revisión. Identificamos que las metodologías permiten una construcción de la solución de manera eficiente mediante fases apoyadas en herramientas, modelos y frameworks para su construcción; siendo la metodología empírica la más utilizada para la construcción de estas soluciones de inteligencia de negocios.

Metodologías para la construcción de soluciones de inteligencia de negocios

The freight transport sector is facing more than ever major innovations and challenges. Digital transformation and analytics tend to optimize traditional work methods and accelerate workflows. This paper focuses on the problem of choosing an analytics solution that allows the prediction of future cases based on historical data and integrates packages that permit to run what-if simulations. Faced with a multitude of criteria required by freight transport professionals, we propose to solve it by implementing the Analytical Hierarchy Process-AHP method. The use of a collaborative approach during the AHP process allowed us to obtain relevant and accurate results. 

A comparative analysis of predictive analytics tools with integrated What-if modules for transport industry

Assim como outros segmentos industriais, os portos e terminais evoluíram, entrando num estágio caracterizado pela transformação digital e adoção de práticas observadas na Indústria 4.0. A partir disto, deu-se origem ao conceito do Porto 4.0, que busca implementar tecnologias que automatizem a realização de tarefas e possibilitem a integração de processos. Assim, discutiu-se a implementação de um sistema de Avaliação de Desempenho Ambiental pautado nos conceitos do Porto 4.0. Como resultado, obteve-se uma proposta de layout, segmentada em três fluxos principais que se sucedem: Planejamento, IoT/Big Data e Business Intelligence and Analytics.

/pdf/avaliacao-de-desempenho-ambiental-no-contexto-do-porto-4-0-vtfcplnh.pdf

Avaliação de desempenho ambiental no contexto do porto 4.0

The article deals with intermodal cargo control with the utilization of Business Intelligence in a shipping company. It comprises of Business Intelligence basis including brief instructions for computer application creation and the mentioned application which is put into practice when controlling cargo of dedicated trains or other types of cargo, which relates to intermodal transport.

Utilization of Business Intelligence Tools in Cargo Control

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Utilization of Business Intelligence Tools in Cargo Control