9th International Conference on ICT for Sustainable Development

Authors - Shailesh Gahane, Aastha Dubey, Pankajkumar Anawade, Deepak Sharma
Abstract - This research paper presents the role of data analytics in artificial intelligence. It talks about how data analytics is incorporated in AI. It delves into the realms of data analytics and predictive modelling, elucidating the distinctions between data analytics and data analysis. The process of gathering, organizing, and transforming data in order to produce forecasts and conclusions for well-informed decision-making is known as data analytics. It highlights the transformative role of technology over decades and how predictive analysis aids in modelling future outcomes. Predictive analytics, a focal point of the discussion, involves the use of data to forecast future results. It employs tools, algorithms, and techniques from machine learning, artificial intelligence, and statistical models to anticipate forthcoming trends. The narrative underlines the significance of predictive modelling across diverse industries, including insurance, marketing, finance, sports, and healthcare. It expounds upon supervised and unsupervised predictive models, which respectively involve labelled and unlabelled datasets. The integration of artificial intelligence into predictive analytics is a central theme. The fusion of AI and predictive modelling empowers businesses to comprehend customer behaviour, enhance sales, and optimize decision-making processes. Machine learning's role is highlighted as it enables machines to learn from data and make informed choices. The advantages of AI-driven approaches, such as reduced human error, constant availability, risk mitigation, and innovative breakthroughs, are detailed. The abstract concludes by underscoring the applications of AI-driven data analytics, highlighting how it enables businesses to gain insights, enhance efficiency, predict demand, and ultimately make more informed decisions. These machines can very accurately replicate human skills thanks to technological advancements. The industries that use big data and artificial intelligence (AI) include those that have benefited from the growing demand for smart production that is safe, affordable, and sustainable, as well as from new technical enablers. Finally, through comprehensive studies and conversations, we investigate the importance of AI and the massive towards 4.0 applications. Finally, through comprehensive studies and conversations, we investigate the importance of AI and the Future studies in the field are anticipated to use this work as a baseline. The paper provides a comprehensive overview of the role of data analytics in artificial intelligence, covering various techniques and approaches. The inclusion of applications of AI-driven data analytics offers practical insights into its implementation.