Springer Handbook of Data Engineering by Xhafa, Fatos;

Sorozatcím: Springer Handbooks;

20% KEDVEZMÉNY?
A kedvezmény csak az 'Értesítés a kedvenc témákról' hírlevelünk címzettjeinek rendeléseire érvényes.

Kiadói listaár EUR 534.99
Az ár azért becsült, mert a rendelés pillanatában nem lehet pontosan tudni, hogy a beérkezéskor milyen lesz a forint árfolyama az adott termék eredeti devizájához képest. Ha a forint romlana, kissé többet, ha javulna, kissé kevesebbet kell majd fizetnie.

208 967 Ft (199 016 Ft + 5% áfa)
Kedvezmény(ek) 20% (cc. 41 793 Ft off)
Kedvezményes ár 167 173 Ft (159 213 Ft + 5% áfa)
A kedvezmény érvényes eddig: 2026. június 30.

183 891 Ft

Beszerezhetőség

Még nem jelent meg, de rendelhető. A megjelenéstől számított néhány héten belül megérkezik.

A termék adatai:

Kiadó Springer Nature Switzerland
Megjelenés dátuma 2026. augusztus 30.
Kötetek száma 1 pieces, Book

ISBN 9783031923715
Kötéstípus Keménykötés
Terjedelem1840 oldal
Méret 279x210 mm
Nyelv angol
Illusztrációk L, 1840 p.

Kategóriák

Hosszú leírás:

"

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.

"

Több

Tartalomjegyzék:

"

PART I: Networking Data.- Part II: Data Analytics.- Part III: HPC Big Data Processing in Cloud Environments..- Part IV: Health Data.- Part V: Finance Data.- Part VI: Quality of Service, Smart Contracts and Blockchain.- Part VII: Sustainable Land Management.- Part VIII: Data Piracy, Data Integreation, Architectures and Services.- Part IX: Data Security.- Part X: Digital Twins and Virtual Reality.- Part XI: Data Quality, Data Lineage/Data Governance.

"