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

Muntean, Mihaela; Dănăiaţă, Doina; Hurbean, Luminiţa; Jude, Cornelia

doi:10.3390/su13020638

Cited by 23 publications

(15 citation statements)

References 34 publications

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“…Affordable and clean energy is directly related to other SDGs [196]. Energy production enhancement, energy efficiency [197,198], alternative energy resources [199], modern and renewable energy [200], clean cooking [201,202], energy cost [203], and zero-carbon energy and greenhouse gasses [204] are just a few highlights of the SDG-7 literature.…”

Section: Sdg-6 (Clean Water and Sanitation)mentioning

confidence: 99%

Sustainable Development Goals (SDGs) as a Framework for Corporate Social Responsibility (CSR)

et al. 2022

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Corporate Social Responsibility (CSR) has been an articulated practice for over 7 decades. Still, most corporations lack an integrated framework to develop a strategic, balanced, and effective approach to achieving excellence in CSR. Considering the world’s critical situation during the COVID-19 pandemic, such a framework is even more crucial now. We suggest subsuming CRS categories under Sustainable Development Goals (SDGs) be used and that they subsume CSR categories since SDGs are a comprehensive agenda designed for the whole planet. This study presents a new CSR drivers model and a novel comprehensive CSR model. Then, it highlights the advantages of integrating CSR and SDGs in a new framework. The proposed framework benefits from both CSR and SDGs, addresses current and future needs, and offers a better roadmap with more measurable outcomes.

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Section: Sdg-6 (Clean Water and Sanitation)mentioning

confidence: 99%

Sustainable Development Goals (SDGs) as a Framework for Corporate Social Responsibility (CSR)

et al. 2022

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“…Only in this way can we bring breakthrough progress to the use of big data [30]. In addition, how to make the perfect combination of big data and enterprise operation and development is a problem that every enterprise needs to think about and constantly improve, and the construction of a perfect business intelligence system plays a supporting role [31][32][33][34].…”

Section: Business Intelligence and Big Datamentioning

confidence: 99%

Evolution of Business Intelligence: An Analysis from the Perspective of Social Network

Yin

Li*

2022

Teh. vjesn.

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Based on CiteSpace, Pajek and other software, this paper makes a visual analysis of the knowledge graph of the related literature of Business Intelligence and explores the future development trend of business intelligence. Taking the core periodicals of CNKI as the data source, key words are drawn and analyzed with the help of software. The total number of articles was 2938 from 2006 to 2020, and the number of articles published in the past 15 years was gradually levelled off. Among the 607 researchers, Yang Bingru is the representative; there are 424 journals, Journal of Information is the first, and 787 keywords are the most frequently used data mining. Our country still needs in-depth research in the field of business intelligence. Through the atlas, it directly shows that big data and machine learning are the frontier hot spots of future development, which provides research direction for researchers.

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“…(a) Oriented to strategic aspects of the sector: Muntean et al (2021) designed a process to develop information artifacts, which are the essence of a business intelligence & analytics system, to monitor the SDG 7 about SDG 13 indicators; Schinkinger (2020) explores how data analytics can be performed in real-time and help companies in decision making, sales, and strategy development by turning data into information and gaining new insights from it for energy suppliers; (Zia et al, 2019) describe outputs which may include the system feasibility, greenhouse gas emissions, cumulative financial costs, natural resource use; (Harison, 2012) based on the analytical framework, possible technical, organisational, and personal factors that affect the failure, partial or full success of BI system implementations are discussed and Argotte et al (2009) present a comprehensive survey related to the BI applications for the Energy Markets (EM) to show trends and useful methods for tackling everyday EM challenges.…”

Section: Business Intelligencementioning

confidence: 99%

Analysis of the energy service in non-interconnected zones of Colombia using business intelligence

et al. 2021

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This work aims to evaluate the provision of energy services in noninterconnected zones (NIZ) between 2018 and 2019 using open data from the Colombian government and business intelligence methodology. The analysis is approached from the ETL (Extract, Transform, Load). It focuses on the variables obtained from the National Monitoring Centre (CNM) for monitoring the operation of these zones, where there is a Telemetry System that provides monthly information on location variables, energy variables, such as active and reactive energy maximum power, maximum power per day, and hours of service delivery. We concluded that in the years, 2018-2019 energy consumption in NIZ has remained stable with a variation of 0.19%. On the other hand, the NIZ include 56% of Colombia's states, and the energy consumption is concentrated in 6 of the 93 municipalities with 80% of national consumption. The challenges in these areas Ramón Fernando Colmenares-Quintero ABOUT THE AUTHORS Ramón Fernando Colmenares-Quintero is currently the national head of research in engineering and Professor Dr. at UCC with research focus on energy generation/distribution, simulation and modelling in the energy field. Gina Maestre-Góngora. Received a PhD degree in systems engineering and computation. Her research interests: Smart Cities, IT Management, Data Analysis, EA, and IT Project Management. Lina Judith Pacheco Moreno She is a student of Software Engineering Program at the UCC. Member of BERSTIC research seedbed participating in projects related to business intelligence applied to energy. Natalia Rojas has a degree in Civil Engineering and an MSc in Marine Renewables, works for Aquatera bringing knowledge and expertise in energy engineering. Kim E. Stansfield got a PhD in Composites from Kingston University. He was sustainable energy systems transformation planner at the UK ETI. Joined Warwick WMG in 2016. Prof. Dr. Juan Carlos Colmenares-Quintero is the leader of the research group CatSEE from the IPC/PAS in Poland. His interests range from materials science/nanotechnology to photocatalysis and water/air purification. PUBLIC INTEREST STATEMENTThis work aims to evaluate the provision of energy services in non-interconnected zones (NIZ) between 2018 and 2019 using open data from the Colombian government and business intelligence approach. The NIZ include 56% of Colombia's states. Their challenges are associated not only with the quality and provision of energy services but also with the environmental challenges that mean that most of these areas obtain their energy supply from fossil fuels, being protected areas such as ecological reserves, the biosphere or the jungle.

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

Cited by 23 publications

References 34 publications

Sustainable Development Goals (SDGs) as a Framework for Corporate Social Responsibility (CSR)

Sustainable Development Goals (SDGs) as a Framework for Corporate Social Responsibility (CSR)

Evolution of Business Intelligence: An Analysis from the Perspective of Social Network

Analysis of the energy service in non-interconnected zones of Colombia using business intelligence

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