American Journal of Advanced Multidisciplinary Research and Innovation

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Integrating Big Data Analytics, Internet of Things, and Cloud Computing for Smart Decision-Making Systems

Author(s) Pattie Maes
Country United States
Abstract The exponential growth of digital technologies has transformed the way organisations collect, process, analyse, and utilise data for intelligent decision-making. The proliferation of the Internet of Things (IoT), Big Data Analytics (BDA), Cloud Computing, Artificial Intelligence (AI), Machine Learning (ML), Edge Computing, Blockchain, and Digital Twin Technology has enabled the development of smart decision-making systems capable of supporting real-time monitoring, predictive analytics, operational optimisation, and strategic planning across multiple sectors. Smart decision-making systems are increasingly applied in healthcare, manufacturing, agriculture, transportation, finance, education, energy management, and smart cities to improve efficiency, sustainability, and organisational resilience. However, the integration of heterogeneous data sources, scalability requirements, cybersecurity risks, privacy concerns, and interoperability challenges remain significant obstacles to effective implementation.
This study presents a comprehensive analysis of integrating Big Data Analytics, Internet of Things, and Cloud Computing for smart decision-making systems. A qualitative analytical research methodology based on secondary data is employed to investigate data acquisition, cloud-based analytics, IoT-enabled sensing, AI-driven predictive modelling, edge intelligence, and intelligent decision support architectures. The research evaluates how integrated digital technologies improve organisational performance, resource optimisation, operational intelligence, and evidence-based decision-making while contributing to sustainable digital transformation.
The findings indicate that combining Big Data Analytics, IoT, and Cloud Computing significantly enhances real-time situational awareness, predictive decision-making, process automation, operational efficiency, and service quality. IoT devices continuously generate large-scale structured and unstructured data, while cloud computing provides scalable storage and computational resources for advanced analytics. Artificial Intelligence further strengthens decision support through anomaly detection, forecasting, optimisation, and intelligent recommendations. Moreover, integrating edge computing, blockchain, and Digital Twin technologies improves latency, security, interoperability, transparency, and resilience across distributed digital ecosystems.
Despite these opportunities, challenges remain concerning data governance, cybersecurity, privacy protection, cloud dependency, communication latency, data quality, infrastructure costs, and workforce readiness. Future research should investigate explainable AI, federated analytics, green cloud computing, quantum-enhanced big data processing, and intelligent autonomous decision-making frameworks.
The study concludes that integrating Big Data Analytics, the Internet of Things, and Cloud Computing provides a robust multidisciplinary foundation for developing scalable, secure, and intelligent decision-making systems capable of supporting sustainable digital transformation across diverse industrial and societal domains
Keywords Big Data Analytics, Internet of Things, Cloud Computing, Smart Decision-Making, Artificial Intelligence, Edge Computing, Digital Transformation, Predictive Analytics, Intelligent Decision Support Systems.
Field Engineering
Published In Volume 2, Issue 1, January-February 2020
Published On 2020-01-04
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