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After the fast development in Internet technologies, data has been coined as the "new oil". Indeed, on the one hand, Internet technologies have enabled gathering and storing unlimited amounts of data in Data Centers and, on the other, Cloud computing ecosystem has enabled unlimited computing capacity for processing and analyzing the data. Data knowledge requires data engineering to enable knowledge integration into decision-making, businesses processes, etc.
Data Engineering addresses building and deployment of distributed, scalable and reliable data infrastructures and integrating them into the knowledge and business pipelines of institutions, organizations, businesses and alike.
The Handbook of Data Engineering provides a comprehensive coverage of the engineering aspects of building and deploying distributed, scalable, secure and reliable data infrastructures for intelligent processing and decision making systems.
List of contents
PART A: Networking Data.- Part B: Data Analytics.- Part C: HPC Big Data and Cloud Applications.- Part D: Health Data.- Part E: Finance Data.- Part F: Quality of Service, Smart Contracts and Blockchain.- Part G: Sustainable Land Management.- Part H: Data Piracy, Data Integreation, Architectures and Services.- Part I: Data Security.- Part J: Digital Twins and Virtual Reality.- Part K: Data Quality, Data Lineage/Data Governance.
About the author
Prof. Dr. Fatos Xhafa is Full Professor (Catedràtic d'Universitat) at the Dept. of Computer Science, Universitat Politècnica de Catalunya, Barcelona, Spain. He received his PhD in Computer Science from the Dept. of CS at BarcelonaTech in 1998. He has held various academic positions at BarcelonaTech and short term positions abroad including Visiting Professorship at University of Surrey and at the University of London, UK and a Research Associate at Drexel University, USA. He is a member of the IMP-Information Modelling Processing Research Group of UPC.
Summary
After the fast development in Internet technologies, data has been coined as the “new oil”. Indeed, on the one hand, Internet technologies have enabled gathering and storing unlimited amounts of data in Data Centers and, on the other, Cloud computing ecosystem has enabled unlimited computing capacity for processing and analyzing the data. Data knowledge requires data engineering to enable knowledge integration into decision-making, businesses processes, etc.
Data Engineering addresses building and deployment of distributed, scalable and reliable data infrastructures and integrating them into the knowledge and business pipelines of institutions, organizations, businesses and alike.
The Handbook of Data Engineering provides a comprehensive coverage of the engineering aspects of building and deploying distributed, scalable, secure and reliable data infrastructures for intelligent processing and decision making systems.
