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The boom in publicly accessible big data sources, such as social networks and the internet of things, is creating new opportunities as well as new technologies and applications to study and understand socioeconomic activities. Visual analytics is promising social sensing approach that helps users effectively identify interesting events and discover hidden patterns, anomalies, and relations from datasets. Big data however also represents a challenge to current data processing and analytical technologies, given the heterogeneity of multi-source data, extremely large data volume and intensive computation impede the efficiency and feasibility of visual analysis. In this chapter, we introduce cutting-edge data storage, computing, and visualization technologies that can tackle these challenges. Data storage and index mechanism optimize query and reduce response time for multi-dimensional big data access; high …