Marinela Mircea

Bucharest University of Economic StudiesRomania

Marinela MIRCEA received her degree in Informatics in Economy from the Academy of Economic Studies, Bucharest in 2003. In February 2009, she finished the doctoral stage. Her PhD thesis is entitled “Business management in digital economy”. She is teaching at Academy of Economic Studies in Bucharest, at Economic Informatics Department since 2003. Her work focuses on programming, information system, business management and Business Intelligence. Dr. Mircea has published over 60 papers and journal articles in computer science, informatics and business management field. She also served as conference organizing chair, member of program committees and reviewed several papers for international conferences. She is the author of one book and coauthor of six books. Sr. Mircea was a member of over 15 research projects, and project manager for the national research project titled “Modern Approaches in Business Intelligence Systems Development for Services-Oriented Organizations Management”.

1books edited

1chapters authored

Latest work with IntechOpen by Marinela Mircea

The work addresses to specialists in informatics, with preoccupations in development of Business Intelligence systems, and also to beneficiaries of such systems, constituting an important scientific contribution. Experts in the field contribute with new ideas and concepts regarding the development of Business Intelligence applications and their adoption in organizations. This book presents both an overview of Business Intelligence and an in-depth analysis of current applications and future directions for this technology. The book covers a large area, including methods, concepts, and case studies related to: constructing an enterprise business intelligence maturity model, developing an agile architecture framework that leverages the strengths of business intelligence, decision management and service orientation, adding semantics to Business Intelligence, towards business intelligence over unified structured and unstructured data using XML, density-based clustering and anomaly detection, data mining based on neural networks.

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