Mastering Azure Analytics : Architecting in the Cloud with Azure Data Lake, HDInsight, and Spark (Paperback)
暫譯: 精通 Azure 分析:使用 Azure Data Lake、HDInsight 和 Spark 在雲端架構
Zoiner Tejada
- 出版商: O'Reilly
- 出版日期: 2017-05-23
- 定價: $1,650
- 售價: 9.5 折 $1,568
- 語言: 英文
- 頁數: 412
- 裝訂: Paperback
- ISBN: 1491956658
- ISBN-13: 9781491956656
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相關分類:
Microsoft Azure、Spark
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相關翻譯:
精通 Azure Analytics|在雲端上使用 Azure Data Lake、HDInsight 與 Spark (Mastering Azure Analytics : Architecting in the Cloud with Azure Data Lake, HDInsight, and Spark) (繁中版)
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商品描述
Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution.
You’ll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs.
- Understand the fundamental patterns of the data lake and lambda architecture
- Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them
- Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs
- Understand where Azure Machine Learning fits into your analytics pipeline
- Gain experience using these services on real-world data that has real-world problems, with scenarios ranging from aviation to Internet of Things (IoT)
商品描述(中文翻譯)
Microsoft Azure 擁有超過 20 種平台即服務(PaaS)產品,可以支持大數據分析解決方案。那麼,哪一個最適合您的專案呢?這本實用的書籍幫助您了解 Azure 服務的廣度,通過將它們組織成一個參考框架,您可以在構建自己的大數據分析解決方案時使用。
您不僅能夠確定哪項服務最適合該工作,還能學習如何實施一個完整的解決方案,該解決方案可擴展、提供人為容錯能力並支持未來需求。
- 了解數據湖和 Lambda 架構的基本模式
- 認識分析數據管道中的標準步驟,並學習如何使用 Azure Data Factory 來協調它們
- 實施數據湖和 Lambda 架構,使用 Azure Data Lake Store、Data Lake Analytics、HDInsight(包括 Spark)、Stream Analytics、SQL Data Warehouse 和 Event Hubs
- 了解 Azure Machine Learning 在您的分析管道中的位置
- 獲得使用這些服務處理現實世界數據的經驗,這些數據具有現實世界的問題,場景範圍從航空到物聯網(IoT)