Data analysis is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets [Wikipedia]. Data analysis and data management both have multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.
Intelligent Data Analysis and Management (IDAM) examines issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

The goal of IDAM 2013 is to gather people from previously disparate communities to provide a stimulating forum for exchange of ideas and results. We invite academic researchers (in information technologies, computer science, business and organizational studies, social studies), as well as information technology companies, industry consultants and practitioners in the fields involved. IDAM 2013 will be held in Kaohsiung, Taiwan. More specialized topics within IDAM include, but are not limited to:

Benchmarking and performance evaluation
Data analytics
Data cleaning, integration, and provenance
Data mining and knowledge discovery
Data models, semantics, and query languages
Data privacy and security
Data streams and sensor networks
Data visualization
Database monitoring and tuning
Databases for emerging hardware
Distributed and parallel databases
Indexing and physical database design
Information extraction
Information retrieval and text mining
Mobile databases
Modeling approximation and uncertainty in databases
Query processing and optimization
Scientific databases
Semi-structured data
Service-oriented computing and cloud data management
Social networks and graph databases
Storage systems
Transaction management