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

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Michael L. Herriman,Marion E. Myhill metadata tools, and registries. Current research data management is built around FAIR data principles: research data must be Findable, Accessible, Interoperable, Reusable. The chapter also reviews Open Science and Open Access principles..Research Data Management has many specifics compared to enter

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Jennifer Sclafani,Alexander Nikolaou production environment. We discuss the importance of using research methods for effectively planning and managing Data Science projects. We also explain importance of applying best practices in DevOps for software development to Data Science projects that defined as DataOps, primarily focused on da

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https://doi.org/10.1007/978-3-030-76900-0r does not have to deal with hardware setup, patching, management, backups etc. All this is taken care of by the service provider. The user can choose from a wide variety of computing instance types that are optimized for different tasks, and can even set up automatic hardware scaling depending on t

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William E. Tunmer,Judith A. Boweycludes discussion the ACID properties of the SQL databases, BASE properties of NoSQL databases, and CAP Theorem for distributed systems applied to NoSQL databases and their classification. The chapter describes examples of the NoSQL databases capable of processing Big Data.

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Yuri Demchenko,Juan J. Cuadrado-Gallego,Marharyta 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

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