Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes.
The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems.
This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.
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Associate Professor at the Department of Information Systems, University of Minho, Portugal Associate Professor at the Department of Information Systems, University of Minho, Senior Researcher of the ALGORITMI Research Centre, and leader of SEMAG, the Software-based Information Systems Engineering and Management Group, at ALGORITMI. Her research interests include Business Intelligence and Analytics, Big Data Analytics, (Big) Data Warehousing, and Online Analytical Processing.
Invited Lecturer in the field of Information Systems, University of Minho, Portugal Invited Lecturer in the field of Information Systems, at the University of Minho. Previous experiences include senior Big Data engineer, researcher, and software developer. He is the (co)author of several scientific and technical publications in the area of Big Data, Data Warehousing and Data Science, and he is constantly looking for new ways of contributing to the community of researchers and practitioners related to these topics.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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