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Architecting data lakes : data management architectures for advanced business use cases /

Many organizations today are succeeding with data lakes, not just as storage repositories but as places to organize, prepare, analyze, and secure a wide variety of data. Management and governance is critical for making your data lake work, yet hard to do without a roadmap. With this ebook, you'...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sharma, Ben (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, [2018]
Edición:Second edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:Many organizations today are succeeding with data lakes, not just as storage repositories but as places to organize, prepare, analyze, and secure a wide variety of data. Management and governance is critical for making your data lake work, yet hard to do without a roadmap. With this ebook, you'll learn an approach that merges the flexibility of a data lake with the management and governance of a traditional data warehouse. Author Ben Sharma explains the steps necessary to deploy data lakes with robust, metadata-driven data management platforms. You'll learn best practices for building, maintaining, and deriving value from a data lake in your production environment. Included is a detailed checklist to help you construct a data lake in a controlled yet flexible way. Managing and governing data in your lake cannot be an afterthought. This ebook explores how integrated data lake management solutions, such as the Zaloni Data Platform (ZDP), deliver necessary controls without making data lakes slow and inflexible. You'll examine: A reference architecture for a production-ready data lake An overview of the data lake technology stack and deployment options Key data lake attributes, including ingestion, storage, processing, and access Why implementing management and governance is crucial for the success of your data lake How to curate data lakes through data governance, acquisition, organization, preparation, and provisioning Methods for providing secure self-service access for users across the enterprise How to build a future-proof data lake tech stack that includes storage, processing, data management, and reference architecture Emerging trends that will shape the future of data lakes.
Notas:Previous edition published: 2016.
Descripción Física:1 online resource (1 volume) : illustrations
Bibliografía:Includes bibliographical references.