Questo prodotto usufruisce delle SPEDIZIONI GRATIS
selezionando l'opzione Corriere Veloce in fase di ordine.
Pagabile anche con Carta della cultura giovani e del merito, 18App Bonus Cultura e Carta del Docente
The Encyclopedia of Big Data Technologies provides researchers, educators, students and industry professionals with a comprehensive authority over the most relevant Big Data Technology concepts. With over 300 articles written by worldwide subject matter experts from both industry and academia, the encyclopedia covers topics such as big data storage systems, NoSQL database, cloud computing, distributed systems, data processing, data management, machine learning and social technologies, data science. Each peer-reviewed, highly structured entry provides the reader with basic terminology, subject overviews, key research results, application examples, future directions, cross references and a bibliography. The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals. In addition, the distinguished, international editorial board of the encyclopedia consists of well-respected scholars, each developing topics based upon their expertise.
Editorial Board:
Sherif Sakr (Editor-in-Chief), Institute of Computer Science, University of Tartu, Tartu, Estonia
Albert Y. Zomaya (Editor-in-Chief), School of Information Technologies, Sydney University, Sydney, Australia
Pramod Bhatotia, School of Informatics, University of Edinburgh, Edinburgh, UK
Rodrigo N. Calheiros, School of Computing, Engineering and Mathematics, Western Sydney University, Penrith, NSW, Australia
Aamir Cheema, Monash University, Australia
Jinjun Chen, School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia
Philippe Cudré-Mauroux, eXascale Infolab, University of Fribourg, Fribourg, Switzerland
Marcos Dias de Assuncao, Inria, LIP, ENS Lyon, Lyon, France
Marlon Dumas, Institute of Computer Science, University of Tartu, Tartu, Estonia
Paolo Ferragina, Department of Computer Science, University of Pisa, Pisa, Italy
George Fletcher, Technische Universiteit Eindhoven, Eindhoven, Netherlands
Olaf Hartig, Linköping University, Linköping, Sweden
Bingsheng He, National University of Singapore, Singapore
Asterios Katsifodimos, TU Delft, Delft, Netherlands
Alessandro Margara, Politecnico di Milano, Milano, Italy
Kamran Munir, Computer Science and Creative Technologies, University of the West of England, Bristol, UK
Behrooz Parhami, Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA, USA
Antonio Pescapè, Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Napoli, Italy
Meikel Poess, Server Technologies, Oracle, Redwood Shores, California, United States
Deepak Puthal, Faculty of Engineering and Information Technologies, School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, NSW, Australia
Tilmann Rabl, Technische Universität Berlin, Database Systems and Information Management Group, Berlin, Germany
Mohammad Sadoghi, University of California, Davis, CA, USA
Timos Sellis, Swinburne University of Technology, Data Science Research Institute, Hawthorn, Victoria, Australia
Domenico Talia, University of Calabria, Italy
Maik Thiele, Database Systems Group, Technische Universität Dresden, Dresden, Saxony, Germany
Yuanyuan Tian, IBM Almaden Research Center, SAN JOSE, CA, United States
Paolo Trunfio, University of Calabria, DIMES, Rende, Italy
Hannes Voigt, Dresden Database Systems Group, Technische Universität Dresden, Dresden, Germany
Matthias Weidlich, Humboldt-Universität zu Berlin, Department of Computer Science, Berlin, Germany
Fatma Özcan, IBM Research – Almaden, San Jose, CA, USA
Sherif Sakr is the Head of Data Systems Group at the Institute of Computer Science, University of Tartu. He received his PhD degree in Computer and Information Science from Konstanz University, Germany in 2007. He received his BSc and MSc degrees in Computer Science from the Information Systems department at the Faculty of Computers and Information in Cairo University, Egypt, in 2000 and 2003 respectively. During his career, Prof. Sakr held appointments in several international and reputable organizations including University of New South Wales, Macquarie University, Data61/CSIRO, Microsoft Research, Nokia Bell Labs and King Saud bin Abdulaziz University for Health Sciences.
Prof. Sakr's research interest is data and information management in general, particularly in big data processing systems, big data analytics, data science and big data management in cloud computing platforms. Prof. Sakr has published more than 100 refereed research publications in international journals and conferences such as: Proceedings of the VLDB endowment (PVLDB), IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), IEEE Transactions on Service Computing (IEEE TSC), IEEE Transactions on Big Data (IEEE TBD), ACM Computing Survey (ACM CSUR), Journal of Computer, Systems and Science (JCSS), Information Systems, Cluster Computing, Grid Computing, IEEE Communications Surveys and Tutorials (IEEE COMST), IEEE Software, Scientometrics, VLDB, SIGMOD, ICDE, EDBT, WWW, CIKM, ISWC, BPM, ER, ICWS, ICSOC, IEEE SCC, IEEE Cloud, TPCTC, DASFAA, ICPE and JCDL. Prof. Sakr Co-authored 5 books and Co-Edited 3 other books in the areas of data and information management and processing. Sherif is an associate editor of the cluster computing journal and Transactions on Large-Scale Data and Knowledge-Centered Systems (TLDKS). He is also an editorial board member of many
Il sito utilizza cookie ed altri strumenti di tracciamento che raccolgono informazioni dal dispositivo dell’utente. Oltre ai cookie tecnici ed analitici aggregati, strettamente necessari per il funzionamento di questo sito web, previo consenso dell’utente possono essere installati cookie di profilazione e marketing e cookie dei social media. Cliccando su “Accetto tutti i cookie” saranno attivate tutte le categorie di cookie. Per accettare solo deterninate categorie di cookie, cliccare invece su “Impostazioni cookie”. Chiudendo il banner o continuando a navigare saranno installati solo cookie tecnici. Per maggiori dettagli, consultare la Cookie Policy.