As technology advances in different sub-domains of computing, data-driven models are becoming increasingly important. The data-dependent world now faces many challenges in terms of data accuracy and data privacy. High-impact advancements include machine learning, artificial intelligence, deep learning and many more. Data is growing exponentially in terms of diversity and complexity. One organization or industry processes over a few million transactions per hour and stores hundreds of billions of data. We live in a world with a great need for more efficient data analysis and processing. Data analytics can reveal hidden patterns, complex relationships, internal information relations, and even segmentation. Data applications have opened up new possibilities in every aspect of our lives. Studying data and its structure, dynamics, and modern data technologies is ongoing. There is a great deal of literature and research on data management, but it does not address the data processing needs. Many studies focus on developing models and systems for analyzing large datasets.<\/p>\r\n\r\n\r\n\r\n
Data analysis leads to application domains that have a systematic impact on decisions. The knowledge gained from the data analysis enables the generation of critical information for multiple domains. In this conference, we review and discuss the latest trends in data management, the opportunities and challenges, and how they have affected organizations to develop effective business and technology strategies and stay up-to-date in data technology. We also highlight current open research directions in data analytics that need further attention.<\/p>\r\n\r\n\r\n\r\n
The proposed conference will discuss topics not limited to<\/strong><\/span><\/p>\r\n\r\n\r\n\r\n Data applications in various domains and activities \r\n\r\n<\/p>\r\n Special issue<\/span><\/strong><\/p>\r\n
Data in cloud
Real-world data processing
Data inaccuracy and reliability issues
Data Ecosystem
Business Analytics
New data analytics techniques
Physical and management challenges
Synthetic data
Data synthesis
Crowdsourcing and Sensing
Data modelling
Deep learning techniques
Data fusion
Descriptive analytics, Diagnostic analytics, Predictive Analytics, and Prescriptive analytics
Machine learning impact on data processing
Network optimization
Data in Biomedical Engineering
Data in Materials science and mechanics
Data handling and applications in domains
Wireless Networking Data Management
Data of Electronic & Embedded Systems
Multi-media Systems Data
Artificial Intelligence Models and Systems Data
E-Computing Data
Renewable Energies Data<\/strong><\/p>\r\n
Publications<\/span><\/strong><\/p>\r\n
\r\n