Developing a Smart, Integrated Artificial Intelligence-Driven Big Data Analytics Model for Business Intelligence in SaaS Products
Jaideep Singh Bhullar
University of British Columbia
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Business intelligence is revolutionized in SaaS products with the integration of Artificial Intelligence and Big Data Analytics. AI-driven BDA manages large volumes of structured and unstructured data with real-time actionable insights for organizations. This paper explores how AI-driven BDA enhances decision-making, operational efficiency, and predictive analytics in SaaS-based BI tools. We discuss different types of machine learning algorithms, data processing techniques, as well as cloud-based architectures that are used for AI-driven SaaS products. In particular, we touch upon the role of AI in data pre-processing, selecting optimal features, and tuning models for accuracy and efficient performance. Evidence from recent study work also demonstrates how accuracy, scalability, and real-time analytics with AI can be improved and enhanced. More important, the paper also identifies specific challenges in implementing AI, such as data privacy issues, computational costs, ethical concerns, and possible biases in AI models. If these challenges can be solved while using all possibilities of AI, businesses will improve their performance and drive competitiveness in their individual markets. Further research directions will be in the advancement of XAI, methods of privacy-preserving AI, and federated learning for enhanced security and efficiency in SaaS-based BI.
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