The International Conference on Data Management, Analytics and Innovation (ICDMAI - 27) features a diverse range of session tracks designed to cover key research areas, emerging trends and interdisciplinary innovations within the field of Data Analytics,Management.
These sessions provide a platform for researchers, academicians, industry professionals and practitioners to present their work, exchange ideas and explore the advancements shaping the future of the domain.
Each track is carefully curated to encourage knowledge sharing, collaboration and meaningful discussion, and is aligned with the United Nations Sustainable Development Goals.
Submit Your AbstractInternational Conference on Data Management, Analytics and Innovation (ICDMAI - 27) 设有多个分会主题,涵盖重要研究领域、前沿趋势与跨学科创新成果。
各分会主题为研究人员、学者、行业专家及实务工作者提供展示研究成果、交流学术思想、探讨领域发展的平台。
每个分会主题均经过精心设置,旨在促进知识共享、学术合作与深入研讨,并与联合国可持续发展目标(SDGs)保持一致。
提交摘要The session tracks of International Conference on Data Management, Analytics and Innovation (ICDMAI - 27) support the following United Nations Sustainable Development Goals through research, collaboration and knowledge exchange.
本次会议的分会主题通过科研、合作与知识交流,支持以下联合国可持续发展目标。
Browse every track scheduled for this conference.
浏览本次会议的全部分会主题。
This track focuses on novel methodologies and frameworks in data analytics that enhance decision-making processes. Contributions may include case studies, theoretical advancements, and practical applications across various industries.
SDG 9
SDG 12
This session addresses the challenges and solutions associated with managing large datasets in organizational contexts. Papers may explore data governance, storage solutions, and the integration of big data into existing systems.
SDG 8
SDG 12
This track examines the use of predictive analytics to forecast trends and behaviors in business environments. Submissions should highlight empirical research, models, and tools that aid in strategic planning.
SDG 8
SDG 9
This session emphasizes the role of data in informing business decisions and strategies. Contributions should explore frameworks, case studies, and the impact of data analytics on organizational performance.
SDG 8
SDG 9
This track investigates the application of machine learning techniques in engineering disciplines. Papers should present innovative applications, challenges faced, and future directions for research.
SDG 9
SDG 12
This session focuses on the importance of data visualization in interpreting complex datasets. Contributions should discuss innovative visualization tools and their effectiveness in enhancing data comprehension.
SDG 4
SDG 9
This track explores the economic implications of data management practices in organizations. Papers may analyze cost-benefit scenarios, investment strategies, and the economic impact of data-driven innovations.
SDG 8
SDG 9
This session addresses the ethical challenges and considerations that arise in data analytics and management. Contributions should focus on frameworks for ethical decision-making and case studies highlighting best practices.
SDG 16
This track examines the intersection of cloud computing technologies and data management strategies. Papers should explore the benefits, challenges, and future trends in leveraging cloud solutions for data analytics.
SDG 9
SDG 12
This session focuses on the methodologies and technologies that enable real-time data processing and analytics. Contributions should highlight advancements, challenges, and applications in various sectors.
SDG 9
SDG 12
This track investigates innovative practices in data governance that ensure data quality and compliance. Papers should present frameworks, case studies, and the role of governance in enhancing data management.
SDG 16
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