The center focuses on the use of big data analytical and knowledge visualization tools for business problem solving, decision making, solutions evaluation, business forecasting, optimization, insight discovery and data presentation. The center applies the big data analytics techniques and methods in social media data and business transaction data for the analysis of intelligent marketing, customer preference, social networks, consumer behaviors, new products, business trends, and customer relationship management. In order to achieve big data and social media analytics goals, informatics including taxonomy, folksonomy, ontology and semantic web are researched in the center. Informatics architecture builds the foundation for big data and social media analytics platforms used in business decision making creation, innovation, and knowledge management.
Big data analytics is a new analytical method combining statistics, data mining, text mining, machine learning, algorithms, rules and logics to exam and analyze a huge volume of data which is in the format of numerical, textual, image, audio and/or video. Big data analytics provides methods to filter, evaluate and select the related data for analysis and discovering unknown correlations, hidden patterns, unforeseen risks and trends emerge from the massaged data to help organizations develop performance solutions for business optimization. A team of professionals is needed for big data analysis. Data engineers in computing focus on data structure, exchange and sharing to develop algorithms for load balancing and optimization in the distributed computing environment. Data scientists in mathematics focus on the design of new mathematical models and algorithms to improve the accuracy rate of the analytical models. Data analysts in business focus on the use of big data analytics tools for data analysis, business interpretation and applying the analyzed/interpreted results in business problem solving, decision making, forecasting, solution generation and business planning.
Consumer shopping behavior has changed, today consumers search social media customer reviews before purchasing. Social media becomes a new channel for product promotion, advertisement and evaluation. The product feedback from social media allows the virtual marketing agent to perform sales analysis, make product recommendations and enhance customer referral. To analyze the social media data, statistical analysis, network analysis, link analysis, topic detection, time series analysis, complexity theory, game theory, neural network, semantic network and knowledge mapping are commonly used big data analytics techniques. Since virtual agent has the characteristics of task-specific, self-organization, autonomy and communications, agent technologies are used to set up the virtual and personalized business environment for product recommendation, intelligent marketing and customer services.
Informatics combines information technology, data standardization, information exchange, sharing and management concepts to support information flow across the organization for more effective and efficient service delivery, business management, planning and decision making. Informatics is a field that covers a wide range of technologies including 1) information architecture, 2) taxonomy, 3) folksonomy, 4) ontology, 5) semantic network, 6) machine learning, 7) natural language processing, 8) language standards, 9) data exchange rules, 10) regulations and architecture, 11) data security, privacy and management. Since social media and big data are comprised of largely unstructured data; informatics is used to build the foundational information architecture for analysis of social media and big data. From this analytics platform, IT-based innovations in customer services delivery and business management can be developed.
With the exponential growth of social media, the internet of things and invention of 5G technologies, the volume of data will become huge and exists in many different formats. Personalized repositories, assistant agents and augmented reality will become the next generation of cyber technologies. Big data visualization provides a human-navigable interface to manipulate and relate data in numerical, textual, image, video and audio formats. Big data ontologies and semantic networks will be increasingly used to organize and visualize data to provide intelligence for people to navigate, filter, locate and relate data for presentation. Big data integrates data mining and prescriptive analytics techniques for data analysis allow data to be discretely identified, extracted related for presentation.