Übersicht			Auf mobile öffnen

Lieferstatus:	Vorankündigung
Veröffentlichung:	ANGEKÜNDIGT (Januar 2027)
Genre:	Naturwissensch., Medizin, Technik
	Cloud Computing / Computational Intelligence / Computersicherheit / Data Analytics / Data and Information Security / Data Centers / Data Engineering / Data ethics / Data Mining / Data Mining and Knowledge Discovery / data privacy and security / HPC Cloud / Künstliche Intelligenz / Networking data / Netzwerksicherheit / Scalable Computing / Wissensbasierte Systeme, Expertensysteme mehr...
ISBN:	9783031923715
EAN-Code:	9783031923715
Verlag:	Springer International Publishing
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 279 mm / B 210 mm / D
Seiten:	1840
Illustration:	L, 1840 p.
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Keine Bewertung vor Veröffentlichung möglich.

Inhalt:

The Springer Handbook of Data Engineering is a comprehensive reference on the principles, technologies, and practices for designing, building, and deploying modern data infrastructures. It addresses the engineering foundations required to transform massive, heterogeneous data into actionable knowledge for intelligent systems and data-driven decision-making. This handbook explores the full spectrum of data engineering challenges, from distributed architectures and cloud-based processing to security, governance, and emerging applications. Thus, the handbook supports the creation and operationalization of modern AI tools, which depend on high-quality, secure, and scalable data pipelines. By integrating diverse aspects of modern data ecosystems into a single comprehensive volume, this handbook establishes itself as a unique reference in the field of data engineering. The content is organized into eleven parts, covering networking data and the foundations of distributed systems, advanced data analytics techniques, and high-performance computing for big data processing in cloud environments. It examines specialized domains such as health data and finance data, and addresses critical topics including quality of service, smart contracts, and blockchain technologies. Further sections explore sustainable land management through data-driven approaches, as well as issues of data piracy, integration, architectures, and services. Security is treated in depth, alongside emerging concepts such as digital twins and virtual reality. Finally, the handbook provides comprehensive coverage of data quality, lineage, and governance to ensure integrity and compliance in complex data ecosystems. With contributions from leading experts, it combines theoretical depth with practical insights, making it an indispensable resource for academics, researchers, and professionals.