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Open Source Data Pipelines for Intelligent Applications /
For decades, businesses have used information about their customers to make critical decisions on what to stock in inventory, which items to recommend to customers, and when to run promotions. But the advent of big data early in this century changed the game considerably. The key to achieving a comp...
| Autores principales: | , , , , |
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| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
O'Reilly Media, Inc.,
2020.
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| Edición: | 1st edition. |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | For decades, businesses have used information about their customers to make critical decisions on what to stock in inventory, which items to recommend to customers, and when to run promotions. But the advent of big data early in this century changed the game considerably. The key to achieving a competitive advantage today is the ability to process and store ever-increasing amounts of information that affect those decisions. In this report, solutions specialists from Red Hat provide an architectural guide to help you navigate the modern data analytics ecosystem. You'll learn how the industry has evolved and examine current approaches to storage. That includes a deep dive into the anatomy of a portable data platform architecture, along with several aspects of running data pipelines and intelligent applications with Kubernetes. Explore the history of open source data processing and the evolution of container scheduling Get a concise overview of intelligent applications Learn how to use storage with Kubernetes to produce effective intelligent applications Understand how to structure applications on Kubernetes in your platform architecture Delve into example pipeline architectures for deploying intelligent applications on Kubernetes. |
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| Descripción Física: | 1 online resource (81 pages) |