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Titlebook: Big Data Infrastructure Technologies for Data Analytics; Scaling Data Science Yuri Demchenko,Juan J. Cuadrado-Gallego,Marharyta Book 2024

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發(fā)表于 2025-3-21 17:11:19 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Big Data Infrastructure Technologies for Data Analytics
期刊簡稱Scaling Data Science
影響因子2023Yuri Demchenko,Juan J. Cuadrado-Gallego,Marharyta
視頻videohttp://file.papertrans.cn/193/192666/192666.mp4
發(fā)行地址Explains how modern cloud-based platforms and tools can be integrated to form a coherent solution with business benefits.Reveals the major Big Data infrastructure technologies that data science and an
圖書封面Titlebook: Big Data Infrastructure Technologies for Data Analytics; Scaling Data Science Yuri Demchenko,Juan J. Cuadrado-Gallego,Marharyta  Book 2024
影響因子.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 im
Pindex Book 2024
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William E. Tunmer,Robert Grieveve their main business goals and get their financial profit and ROI (Return On Investment). This will typically require some investments both in Big Data Infrastructure (computer hardware and software), business process adjustment/re-organisation and staff development or hiring.
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https://doi.org/10.1007/978-3-030-76900-0eful results such as hidden patterns and relationships in the data. We will provide the mathematical foundations of data validation, along with practical recommendations for its effective implementation.
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