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Business Intelligence for Agricultural Foreign Trade: Design and Application of Power BI Dashboard

Author

Listed:
  • Karen Guadalupe Sanabia-Lizarraga

    (Campos Bórquez, Ciudad Obregon 85010, Mexico)

  • Blanca Carballo-Mendívil

    (Industrial Engineering Department, Sonora Institute of Technology, Ciudad Obregon 85130, Mexico)

  • Alejandro Arellano-González

    (Industrial Engineering Department, Sonora Institute of Technology, Ciudad Obregon 85130, Mexico)

  • Alfredo Bueno-Solano

    (Industrial Engineering Department, Sonora Institute of Technology, Ciudad Obregon 85130, Mexico)

Abstract

In today’s rapidly evolving business landscape, data analytics has become a critical tool for organizations striving to remain competitive and make informed decisions. Although technology facilitates data analysis, many decision-makers need more technical knowledge to use these tools. This project focuses on developing a business intelligence system in Power BI to analyze agricultural exports from Mexico as part of the Agro-logistics Observatory, aiming to bridge this gap and make data more accessible for non-technical users. The objective is to create an interactive panel that would allow users to visualize and compare export and import data, thereby supporting decision-making for both business and academic purposes. The methodology involved collecting and cleaning data from various sources, such as public institutions, and a modeling process that integrates geospatial data and economic classifications. Key performance indicators (KPIs), such as trade balance and the export share by-product, were designed and calculated to identify critical products and trade patterns. Although similar approaches have been presented in the literature, the novelty of this research lies in the detailed presentation of its methodology, which provides a step-by-step guide for its replication that is often lacking in other studies. In addition, it offers a dashboard that integrates data from various sources, presenting them through easy-to-interpret visualizations so that stakeholders can quickly and efficiently access valuable information beyond traditional data visualization. Furthermore, the project highlights opportunities for improvements in data visualization, including integrating more specific product data and enhancing the dashboard’s capabilities through predictive analysis.

Suggested Citation

  • Karen Guadalupe Sanabia-Lizarraga & Blanca Carballo-Mendívil & Alejandro Arellano-González & Alfredo Bueno-Solano, 2024. "Business Intelligence for Agricultural Foreign Trade: Design and Application of Power BI Dashboard," Sustainability, MDPI, vol. 16(21), pages 1-25, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9576-:d:1513187
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    References listed on IDEAS

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    1. Nombulelo Gumata & Eliphas Ndou, 2019. "Accelerated Land Reform, Mining, Growth, Unemployment and Inequality in South Africa," Springer Books, Springer, number 978-3-030-30884-1, December.
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