(BDBI’ ) 2018 - International Workshop on Big Data and Business Intelligence

Big Data Analytics
◦ Storage, Data, and Analytics Clouds
◦ Federal Big Data Cloud Configuration, Performance, and Capacity
◦ Big Data Search
◦ Big Data applications: Bioinformatics, Multimedia, Smartphones, etc.
◦ Data mining, graph mining and data science
◦ Cloud and grid computing for Big Data
◦ Hardware/software infrastructure for Big Data
◦ Role of Big Data issues in Pervasive Systems
◦ Data Mining Techniques in Wireless Sensor Networks
◦ Big Data Analytics applied to Smart Cities
◦ Role of Big Data issues in Vehicle Ad Hoc Networks ..
◦ Challenges and opportunities for the electric energy industry
◦ Big Data advantages for electric energy trading
◦ Big Data and Energy Systems Integration
◦ Big Data and Energy Efficiency
◦ Big Data and Electricity Demand Forecasting
◦ Big Data and Energy Management
◦IA and information systems
◦ ICT integration in education
◦ Information and knowledge management
◦ Information hiding and watermarking
◦ Information technologies
◦ Information theory/coding
◦ Architectures for Big Data
◦ The role of Big Data in improving power system operation and protection
◦ Smart electrical grid with Big Data
◦ Image Processing and Reconstruction
◦Signal Processing
◦ Video Processing and Reconstruction
◦Architecture, management and process for data science
◦Cloud computing and service data analysis
◦Data warehouses, cloud architectures
◦Mathematical Issues in Data Science
◦Big Data Issues and Applications
◦Large-scale databases
◦High performance computing for data analytics
◦Large scale optimization
◦Data-driven Scientific Research
◦Security, trust and risk in big data
◦Privacy and protection standards and policies
◦Data Quality
◦Evaluation and Measurement in Data Science
◦Big Data Mining and Knowledge Management
◦Case Study of Data Science
◦trends and innovative applications of Business Intelligence
◦digitalization and big data
◦benefits of predictive and advanced analytics
◦BI organization – best practices and no-goes.
◦Develop a foundation of business trust through data quality, security, privacy, and governance
◦Make analytics and insight part of the DNA for every person, action, business process and decision
◦Build and execute a world-class, disruptive data and analytics strategy
◦Drive innovation through leading technologies – AI, machine learning, blockchain, Virtual/Augmented Reality, IoT and digital twins
◦Modernize your infrastructure and adopt new architectural approaches to support digital transformation
◦Exploit diverse datasets, diverse teams and diverse thinking to innovate business models
◦Lead by enabling the right culture, people, skills and organization
◦Accelerate the adoption of new skills, new roles, (such as Chief Data Officer), new ways of working and new data-driven thinking