Data Engineering on Azure
暫譯: Azure上的數據工程
Riscutia, Vlad
- 出版商: Manning
- 出版日期: 2021-08-17
- 定價: $1,650
- 售價: 9.0 折 $1,485
- 語言: 英文
- 頁數: 336
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1617298921
- ISBN-13: 9781617298929
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相關分類:
Microsoft Azure
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相關翻譯:
機器學習大數據平臺的構建、任務實現與數據治理——使用Azure、DevOps、MLOps (簡中版)
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商品描述
Data Engineering on Azure teaches you to build a scalable and robust data platform to industry-leading standards. There's a big gap between running machine learning and data processes as prototypes, and deploying them to a production cloud environment. Data Engineering on Azure reveals the architectural, operational, and data management techniques that power cloud-based data infrastructure built on the Microsoft Azure platform. Data Engineering on Azure teaches you to build a scalable and robust data platform to industry-leading standards. All examples are based on the production big data platform that powers Microsoft's customer-growth operations. You'll learn techniques and best practices that author Vlad Riscutia and his team use on a daily basis, including automation and DevOps, running a reliable machine learning pipeline, and managing your data inventory. Examples are illustrated with Azure. The patterns and techniques are transferable to other cloud platforms. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
商品描述(中文翻譯)
《Data Engineering on Azure》教你如何建立一個可擴展且穩健的數據平台，以達到行業領先的標準。
在運行機器學習和數據處理作為原型之間，與將其部署到生產雲環境之間存在著一個巨大的差距。《Data Engineering on Azure》揭示了支撐基於 Microsoft Azure 平台的雲端數據基礎設施的架構、運營和數據管理技術。
《Data Engineering on Azure》教你如何建立一個可擴展且穩健的數據平台，以達到行業領先的標準。所有示例均基於支撐 Microsoft 客戶增長運營的生產大數據平台。你將學習到作者 Vlad Riscutia 及其團隊日常使用的技術和最佳實踐，包括自動化和 DevOps、運行可靠的機器學習管道，以及管理你的數據庫存。示例以 Azure 為例進行說明。這些模式和技術可轉移到其他雲平台。
購買印刷書籍可獲得 Manning Publications 提供的免費電子書，格式包括 PDF、Kindle 和 ePub。
作者簡介
Vlad Riscutia is a software architect at Microsoft.
作者簡介(中文翻譯)
Vlad Riscutia 是微軟的軟體架構師。
