Abstract

The emergence of information based technologies had never been witnessed before and it has restructured the decision making process in industries, particularly in the attempt to combine big data analytics and software engineering solutions. This paper discusses the possibility of intelligent, accurate and dynamic decision making with the help of the big data analytics, which can be incorporated into the modern software engineering practices. Big data analytics based on the five dimensions of volume, velocity, variety, veracity, and value are the foundation of generating anything of use out of complex data. This coupled with software engineering innovations including agile engineering Devops pipelines, microservices and cloud-native architecture will ensure development of scalable, reliable, and performance decision-support systems. It is a literature review conducted systematically, the drawbacks of conventional decision-making frames, and the presentation of a conceptual framework that integrates analytics pipelines and software lifecycles of engineering. The research indicates that comparative measures and case studies of the field of healthcare, finance, and governance give increases in decision accuracy, efficiency, and adaptability. The outcome of the study shows that intelligent systems of decision-making may not only minimize risks of operation, but also optimize the forecasting outcome to develop a new level of organizational intelligence, and may encourage the privacy-saving approach and independence of the machine-based learning forecasts. Finally, it highlights its future, which is the application of edge and quantum computing, advanced predictive modeling and autonomous software systems all these are bound to revolutionize the dynamic decision making environment. It is applicable to the academic and industrial process since the study offers a blueprint of how the big data analytics may be integrated into innovations in software engineering so as to come up with robust and intelligent decision-support systems

Keywords

  • Predictive Analytics
  • Intelligent Decision-Making Systems
  • Software Engineering Innovations
  • Big Data Analytics

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