Azure Storage, Streaming, and Batch Analytics: A guide for data engineers
暫譯: Azure 儲存、串流與批次分析：數據工程師指南
Nuckolls, Richard
- 出版商: Manning
- 出版日期: 2020-11-10
- 售價: $1,750
- 貴賓價: 9.5 折 $1,663
- 語言: 英文
- 頁數: 375
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1617296309
- ISBN-13: 9781617296307
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相關分類:
Microsoft Azure
立即出貨 (庫存 < 4)
商品描述
The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage.
Azure Data Engineering teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system.
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)
微軟的 Azure 雲端平台是數據密集型應用的理想選擇。Azure 旨在提高生產力，提供預建的服務，使數據的收集、存儲和分析變得更容易實施和管理。
《Azure 數據工程》教您如何在 Azure 中設計一個可靠、高效且具成本效益的數據基礎設施，通過逐步構建一個完整的工作分析系統。
購買印刷版書籍可免費獲得 Manning Publications 提供的 PDF、Kindle 和 ePub 格式的電子書。
作者簡介
Richard Nuckolls is a senior developer building a big data analytics and reporting system in Azure. During his nearly 20 years of experience, he's done server and database administration, desktop and web development, and more recently has led teams in building a production content management system in Azure.
作者簡介(中文翻譯)
Richard Nuckolls 是一位資深開發人員，正在 Azure 中構建大數據分析和報告系統。在近 20 年的經驗中，他曾從事伺服器和資料庫管理、桌面和網頁開發，最近則領導團隊在 Azure 中構建生產內容管理系統。
目錄大綱
1. What is data engineering
2 Building an analytics system in Azure
3 Azure Storage Blob service
4 Azure Data Lake storage
5 Message handling with Event Hubs
6 Real-time queries with Azure Stream Analytics
7 Batch queries with Azure Data Lake Analytics
8 U-SQL for complex analytics
9 Integrating with Azure Data Lake Analytics
10 Service integration with Azure Data Factory
11 Managed SQL with Azure SQL Database
12 Integrating Data Factory with SQL Database
13 Where to go next
A Appendix A. Set up of Azure resources through Powershell
目錄大綱(中文翻譯)
1. What is data engineering
2 Building an analytics system in Azure
3 Azure Storage Blob service
4 Azure Data Lake storage
5 Message handling with Event Hubs
6 Real-time queries with Azure Stream Analytics
7 Batch queries with Azure Data Lake Analytics
8 U-SQL for complex analytics
9 Integrating with Azure Data Lake Analytics
10 Service integration with Azure Data Factory
11 Managed SQL with Azure SQL Database
12 Integrating Data Factory with SQL Database
13 Where to go next
A Appendix A. Set up of Azure resources through Powershell
