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Big Data Infrastructure Technologies for Data Analytics

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Big Data Infrastructure Technologies for Data Analytics
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41,19 USD
Typical price538,94 PLN
Lowest (90 days)41,19 PLN
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2026-08-08 2026-08-15
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2026-08-0841,19
2026-08-1541,19
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SP SpringerNatureLink Shop INT 41,19 USD free 41,19 USD Disponible il y a 3 jours View offer
SP SpringerNatureLink Shop INT 14 299,00 JPY 29,00 JPY 14 328,00 JPY Disponible il y a 3 jours View offer
SP Springer Nature Author 14 299,00 JPY free 14 299,00 JPY Disponible il y a 1 semaine View offer
SP SpringerNatureLink Shop INT 99,99 USD free 99,99 USD Disponible il y a 3 jours View offer
SP SpringerNatureLink Shop INT 109,99 USD 25,00 USD 134,99 USD Disponible il y a 3 jours View offer
SP SpringerNatureLink Shop INT 109,99 USD free 109,99 USD Disponible il y a 3 jours View offer
SP SpringerNatureLink Shop INT 118,00 EUR 29,00 EUR 147,00 EUR Disponible il y a 3 jours View offer

Les prix et la disponibilité peuvent changer. Dernière mise à jour: 08.08.2026 21:59.

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This book provides a comprehensive overview and introduction to Big Data Infrastructure technologies, existing cloud-based platforms, and tools for Big Data processing and data analytics, combining both a conceptual approach in architecture design and a practical approach in technology selection and project implementation. Readers will learn the core functionality of major Big Data Infrastructure components and how they integrate to form a coherent solution with business benefits. Specific attention will be given to understanding and using the major Big Data platform Apache Hadoop ecosystem, its main functional components MapReduce, HBase, Hive, Pig, Spark and streaming analytics. The book includes topics related to enterprise and research data management and governance and explains modern approaches to cloud and Big Data security and compliance. The book covers two knowledge areas defined in the EDISON Data Science Framework (EDSF): Data Science Engineering and Data Management and Governance and can be used as a textbook for university courses or provide a basis for practitioners for further self-study and practical use of Big Data technologies and competent evaluation and implementation of practical projects in their organizations.

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