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Big Data Analytics for Sustainable Technology Development

Author(s) Prof. Per Skoglund
Country Sweden
Abstract The rapid expansion of digital technologies has generated unprecedented volumes of structured and unstructured data across industrial, environmental, economic, and social systems. Big Data Analytics (BDA) provides organizations and technology developers with the ability to transform these large and complex datasets into actionable knowledge for improving resource efficiency, technological innovation, environmental monitoring, and sustainable development. This study examines the role of Big Data Analytics in supporting sustainable technology development and proposes a conceptual framework connecting data acquisition, data management, analytical processing, intelligent decision-making, technology optimization, and sustainability outcomes. A conceptual and descriptive research design is adopted through a structured synthesis of secondary scholarly literature concerning Big Data Analytics, sustainable technologies, digital transformation, smart systems, resource optimization, circular economy, energy management, and environmental sustainability. Existing research indicates that Big Data Analytics can contribute to sustainability by improving energy forecasting, optimizing resource consumption, supporting sustainable production, reducing waste, strengthening supply-chain efficiency, and enabling data-driven environmental decision-making. Recent literature also emphasizes the importance of combining Big Data Analytics with artificial intelligence, Internet of Things technologies, cloud computing, and other digital infrastructures to support sustainable technological ecosystems.
The analysis identifies data quality, technological infrastructure, analytical capability, organizational readiness, governance, cybersecurity, and environmental cost as important factors influencing successful implementation. The study further highlights that Big Data Analytics should not be treated merely as a technical tool but as an integrated capability that connects technological innovation with environmental, economic, and social objectives. The proposed framework demonstrates how analytics can support sustainable technology development across the technology life cycle, from planning and design to implementation, monitoring, optimization, and continuous improvement. The study concludes that responsible and strategically aligned Big Data Analytics can strengthen sustainable technological development by improving decision quality, reducing resource waste, supporting innovation, and enabling more adaptive and resilient systems.
Keywords Big Data Analytics, Sustainable Technology, Sustainable Development, Data-Driven Innovation, Resource Optimization, Digital Transformation, Green Technology, Environmental Sustainability, Smart Systems, Circular Economy
Field Engineering
Published In Volume 2, Issue 1, January-February 2020
Published On 2020-01-28
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