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A Business Intelligence & Analytics Framework for Clean and Affordable Energy Data Analysis

Author

Listed:
  • Mihaela Muntean

    (Department of Business Information Systems, West University of Timisoara, 300223 Timisoara, Romania)

  • Doina Dănăiaţă

    (Department of Business Information Systems, West University of Timisoara, 300223 Timisoara, Romania)

  • Luminiţa Hurbean

    (Department of Business Information Systems, West University of Timisoara, 300223 Timisoara, Romania)

  • Cornelia Jude

    (Flat White Economy Investment, 020335 Bucuresti, Romania)

Abstract

Energy is the sector most strongly connected with climate change moderation, and this correlation and interdependency is largely investigated, in particular as regards renewable energy and sustainability issues. The United Nations, European Union, and all countries around the world declare their support for sustainable development, materialized in agreements, strategies, and action plans. This diversity, combined with significant interdependencies between indicators, brings up challenges for data analysis, which we have tackled in order to decide on relevant indicators. We have built a research framework based on Business Intelligence & Analytics for monitoring the SDG7 indicators that aim at “Ensuring access to affordable, reliable, sustainable, and modern energy for all”, in relation with SDG13 indicators targeting the sustainable aspect of energy. In developing the Business Intelligence & Analytics framework, we have considered Design Science Research in information systems guidelines. We have designed a process for carrying out Design Science Research by describing the demarche to develop information artifacts, which are the essence of a Business Intelligence & Analytics system. The information artifacts, such as data source, preprocessed data, initial and final data model, as well as data visualizations, are designed and implemented in order to support clean and affordable energy data analysis. The proposed research model, applied for Romania in this paper, serves as a point of departure for investigating data in a more integrated way, and can be easily applied to another country case study.

Suggested Citation

  • Mihaela Muntean & Doina Dănăiaţă & Luminiţa Hurbean & Cornelia Jude, 2021. "A Business Intelligence & Analytics Framework for Clean and Affordable Energy Data Analysis," Sustainability, MDPI, vol. 13(2), pages 1-25, January.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:2:p:638-:d:478433
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    References listed on IDEAS

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    1. Fatih Gurcan & Ahmet Ayaz & Gonca Gokce Menekse Dalveren & Mohammad Derawi, 2023. "Business Intelligence Strategies, Best Practices, and Latest Trends: Analysis of Scientometric Data from 2003 to 2023 Using Machine Learning," Sustainability, MDPI, vol. 15(13), pages 1-23, June.

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