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Big Data Infrastructure Technologies For Data Analytics Scaling Data Science Applications For Continuous Growth 2024th Edition Yuri Demchenko

  • SKU: BELL-63703022
Big Data Infrastructure Technologies For Data Analytics Scaling Data Science Applications For Continuous Growth 2024th Edition Yuri Demchenko
$ 31.00 $ 45.00 (-31%)

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Big Data Infrastructure Technologies For Data Analytics Scaling Data Science Applications For Continuous Growth 2024th Edition Yuri Demchenko instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 47.24 MB
Pages: 902
Author: Yuri Demchenko, Juan J. Cuadrado-Gallego, Oleg Chertov, Marharyta Aleksandrova
ISBN: 9783031693656, 3031693655
Language: English
Year: 2024
Edition: 2024

Product desciption

Big Data Infrastructure Technologies For Data Analytics Scaling Data Science Applications For Continuous Growth 2024th Edition Yuri Demchenko by Yuri Demchenko, Juan J. Cuadrado-gallego, Oleg Chertov, Marharyta Aleksandrova 9783031693656, 3031693655 instant download after payment.

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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