This track focuses on the latest advancements in machine learning algorithms tailored for big data applications. Researchers are encouraged to present novel approaches that enhance predictive accuracy and computational efficiency.

This session explores comprehensive governance frameworks designed to manage big data effectively within organizations. Discussions will center on best practices, compliance, and the integration of governance into data management strategies.

This track highlights the development of intelligent systems that facilitate efficient data processing in large-scale environments. Contributions should focus on the interplay between machine learning techniques and automation in data workflows.

This session examines the role of cloud computing in providing scalable solutions for big data analytics. Researchers are invited to discuss architectures and technologies that support large-scale data storage and processing.

This track delves into the integration of artificial intelligence in business intelligence systems. Presentations should address how AI enhances decision-making processes through advanced analytics and real-time data insights.

This session focuses on methodologies for performance monitoring in big data systems. Researchers are encouraged to share innovative techniques for ensuring system reliability and efficiency in data-intensive applications.