Dr. Rasha Ragheb Attaallah is a lecturer in the Department of Computer Science at the Faculty of Computer Science and Information Technology, University of Malaya. With over 10 years of teaching experience, she has made significant contributions to computer science education and research.
Dr. Rasha holds a PhD in Artificial Intelligence from the University of Malaya, Malaysia, and a master’s degree in Computer Science from the Islamic University in Palestine. She is an expert in AI, neural networks, image processing, and big data analytics.
With extensive experience in both academia and industry, Dr. Rasha has led research initiatives in AI-driven data processing, predictive analytics, and operational research. Her work spans diverse domains, including healthcare, finance, and smart technologies, where she explores the intersection of AI, machine learning, and big data to drive innovation and enhance decision-making.
Dr. Rasha has also contributed to the development of AI-based assessment tools and has worked on projects involving federated learning, Edge AI, and cloud computing. Passionate about mentoring the next generation of AI professionals, she actively fosters industry-academia collaboration to bridge the gap between research and real-world applications.
As a keynote speaker, Dr. Rasha shares valuable insights into the transformative power of AI in big data analytics. Her engaging presentations translate complex AI concepts into actionable strategies, equipping audiences with the knowledge to leverage AI for data-driven success in an increasingly digital world.
The Future of AI-Driven Big Data Analytics: Trends and Challenges
The Impact of AI on Big Data Analytics: Opportunities and Challenges
In the digital era, the convergence of Artificial Intelligence (AI) and Big Data Analytics is reshaping industries by unlocking new efficiencies, insights, and decision-making capabilities. AI-driven analytics enables organizations to process vast and complex datasets at unprecedented speeds, uncovering hidden patterns, predicting trends, and optimizing operations. From machine learning and deep learning to natural language processing and computer vision, AI technologies are transforming traditional data analysis, making it more automated, accurate, and insightful.
This session explores the opportunities and challenges of integrating AI into Big Data Analytics. We will examine real-world applications across various sectors, including healthcare, finance, retail, and manufacturing, highlighting how AI enhances predictive analytics, real-time decision-making, and data visualization. However, despite its potential, AI-driven analytics faces data quality issues, scalability challenges, ethical concerns, and a shortage of skilled professionals.
By addressing these challenges with advanced data management techniques, cloud computing solutions, bias mitigation strategies, and workforce development initiatives, organizations can fully leverage the power of AI in analytics. As we look to the future, emerging technologies like quantum computing and federated learning promise to further revolutionize AI-driven analytics, positioning data as a key driver of innovation and competitive advantage.
This session will provide insights into best practices, industry trends, and strategic approaches for harnessing AI in Big Data Analytics, empowering organizations to thrive in an increasingly data-driven world.