Marinela Mircea

Bucharest University of Economic Studies

Dr. Marinela Mircea received her degree in Informatics in Economy from the Bucharest University of Economic Studies in 2003. In February 2009, she finished the doctoral stage. Her Ph.D. thesis is entitled "Business management in digital economy”. She is teaching at the University of Economic Studies in Bucharest, at the Economic Informatics Department since 2003. Her work focuses on programming, information systems, business management, and Business Intelligence. Dr. Mircea has published over 70 papers in computer science, informatics and business management field. She has also served as a conference organizing chair, member of program committees and reviewed papers for international conferences and journals. She is the author of two books and a co-author of 17 books. Dr. Mircea was a member of over 15 research projects, and project manager for two national research projects. In June 2016, she has received the habilitation in the field of economic informatics. Since 2016, she is the Professor at the Economic Informatics and Cybernetics Department from The Bucharest University of Economic Studies, Bucharest, Romania.

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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