Big Data Infrastructure Technologies for Data Analytics
Scaling Data Science Applications for Continuous Growth
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Beschreibung
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.
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.
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 analytics developers need to know Useful for students to practitioners for competent evaluation and implementation of Big Data projects in organizations
Autor*in
Yuri Demchenko
Themen in »Big Data Infrastructure Technologies for Data Analytics«
Big Data Big Data Analytics Data Science Large scale data driven applications Big Data Reference Architecture Data Science Analytics Cloud Computing EDISON Data Science Framework (EDSF) Cloud Computing Data Lakes Big Data Algorithms MapReduce Hadoop ecosystem Hadoop File System (HDFS Streaming Analytics