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Big Data Infrastructure Technologies for Data Analytics

Scaling Data Science Applications for Continuous Growth

Specificaties
Gebonden, blz. | Engels
Springer Nature Switzerland | e druk, 2024
ISBN13: 9783031693656
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Springer Nature Switzerland e druk, 2024 9783031693656
€ 108,99
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Samenvatting

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.

Specificaties

ISBN13:9783031693656
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Switzerland

Inhoudsopgave

<p>Chapter 1 Introduction. - Chapter 2&nbsp;Big Data Technologies Foundation: Definition, Reference Architecture, use cases. - Chapter 3&nbsp;Cloud Computing Foundation: Definition, Reference Architecture, Foundational Technologies, Use cases. - Chapter 4&nbsp;Cloud and Big Data Service Providers and Platforms. - Chapter 5&nbsp;Big Data Algorithms, MapReduce<br>
and Hadoop ecosystem.- Chapter 6&nbsp;Streaming Analytics and Spark.- Chapter 7&nbsp;Data Structures for Big Data, Modern Big Data SQL and NoSQL Databases.-Chapter 8&nbsp;Enterprise Data&nbsp;Governance and Management.- Chapter 9&nbsp;Research Data Management.- Chapter 10 Big Data Security and&nbsp;Compliance, Data Privacy Protection.- Chapter 11&nbsp;Finding Data on the Web, Data&nbsp;sets, Web Scraping, Web API.- Chapter 12&nbsp;Data Science Projects Management,DataOps, MLOPs.- Chapter13&nbsp;Data Science Projects Development with Amazon SageMaker.- Chapter 14&nbsp;Data Validation&nbsp;for Data Science Projects.</p>

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        Big Data Infrastructure Technologies for Data Analytics