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Operationalizing the data lake : building and extracting value from data lakes with a cloud-native data platform /

Big data and advanced analytics have increasingly moved to the cloud as organizations pursue actionable insights and data-driven products using the growing amounts of information they collect. But few companies have truly operationalized data so it's usable for the entire organization. With thi...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ackerman, Holden (Autor), King, Jon (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, [2019]
Edición:First edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a Big data and advanced analytics have increasingly moved to the cloud as organizations pursue actionable insights and data-driven products using the growing amounts of information they collect. But few companies have truly operationalized data so it's usable for the entire organization. With this pragmatic ebook, engineers, architects, and data managers will learn how to build and extract value from a data lake in the cloud and leverage the compute power and scalability of a cloud-native data platform to put your company's vast data trove into action. Holden Ackerman and Jon King of Qubole take you through the basics of building a data lake operation, from people to technology, employing multiple technologies and frameworks in a cloud-native data platform. You'll dive into the tools and processes you need for the entire lifecycle of a data lake, from data preparation, storage, and management to distributed computing and analytics. You'll also explore the unique role that each member of your data team needs to play as you migrate to your cloud-native data platform. Leverage your data effectively through a single source of truth Understand the importance of building a self-service culture for your data lake Define the structure you need to build a data lake in the cloud Implement financial governance and data security policies for your data lake through a cloud-native data platform Identify the tools you need to manage your data infrastructure Delineate the scope, usage rights, and best tools for each team working with a data lake--analysts, data scientists, data engineers, and security professionals, among others. 
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