International Conference on Big Data Analysis and Application (ICBDAA 2026)

The International Conference on Big Data Analysis and Application (ICBDAA 2026) explores advancements and applications of big data technologies, analytics, and AI across various industries and domains.

Key Topics

• Big Data Applications
  • New domains and novel applications related to Big Data technologies
  • Representation Formats for Multimedia Big Data
  • Big Data for Internet of Things (IoT)
  • Scientific Applications of Big Data
  • Green Computing and Networking Technologies for Cloud and Big Data
  • Government and Industrial Experiences for Cloud and Big Data
  • Big Data Analysis for Business Model Innovation
  • Big Data Education
  • Big Data Analysis Economics
  • Big Data Analysis for Enterprise, Government and Society
  • Big Data for Business Model Innovation
  • Big data applications: Bioinformatics
  • Big Data for Vertical Industries (including Government, Healthcare, and Environment)
  • Big Data for Enterprise Transformation
  • Machine learning and AI for big data
  • Big Data in Smart Planet Solutions
  • SME-centric Big Data Analytics
  • Real-life Case Studies of Value Creation through Big Data Analytics
  • Software Engineering for Cloud Computing and Big Data
• Big Data Analysis
  • Big Data Analysis Encryption
  • Big Data Analysis Search and Mining
  • Big Data Analysis Analytics and Metrics
  • Big Data Analysis Management
  • Big Data Processing and Querying
  • Big Data Analysis Architectures
  • Evolutionary and Bio-inspired approaches for Big Data analysis
  • Data Visualization and Visual Analytics
  • Machine learning based on Big Data
  • Big Data Visualization
  • Big data analytics and social media
  • Big Data Analysis Search and Mining
  • Visualization Analytics for Big Data
  • Data mining, graph mining and data science
  • Cloud Computing Techniques for Big Data
  • Big Data Models and Algorithms
  • Big Data Search and Mining
  • Big Data in Mobile and Pervasive Computing
  • Novel Computational Intelligence approaches for data analysis