Strategic financial decision-making in sustainable energy investments: Leveraging big data for maximum impact

Omowonuola Ireoluwapo Kehinde Olanrewaju 1, *, Gideon Oluseyi Daramola 2 and Darlington Eze Ekechukwu 3

1 Independent Researcher, Fort Worth, Dallas, USA.
2 Independent Researcher, Lagos, Nigeria.
3 Independent Researcher, UK.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(03), 564–573
Article DOI: 10.30574/wjarr.2024.22.3.1758
Publication history: 
Received on 01 May 2024; revised on 08 June 2024; accepted on 10 June 2024
In the context of escalating environmental concerns and the transition towards a greener economy, sustainable energy investments have emerged as a pivotal area for financial growth and innovation. This paper outlines a strategic framework for financial decision-making in sustainable energy investments, emphasizing the transformative role of big data. By integrating big data analytics into the investment process, stakeholders can enhance market analysis, risk assessment, performance monitoring, and predictive modeling, leading to more informed and effective investment strategies. The paper delves into various big data sources, analytical tools, and technologies that facilitate the collection, processing, and interpretation of vast amounts of information. Additionally, it presents case studies illustrating successful applications of big data in solar and wind energy projects, highlighting best practices and common challenges. The discussion extends to future trends, including advancements in artificial intelligence and machine learning, which are poised to further revolutionize the sector. The paper concludes with strategic recommendations for developing a data-driven investment approach, building robust data infrastructures, and fostering a culture of continuous learning and adaptation. By leveraging big data, investors can maximize the impact of their investments, drive sustainable growth, and contribute to the global energy transition.
Sustainable Energy Investments; Big Data Analytics; Strategic Financial Decision-Making; Market Analysis; Risk Assessment; Predictive Modeling.
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