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Databases in Azure

开始时间: 04/22/2022 持续时间: 4 weeks

所在平台: EdxArchive

课程类别: 其他类别

大学或机构: Microsoft

授课老师: Cynthia Staley Tony Jamieson Corey Hynes

课程主页: https://www.edx.org/archive/databases-azure-microsoft-azure207x

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课程详情

This course focuses primarily on Azure SQL Database as a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

You’ll be introduced to data services that Azure provides to store, manage, and analyze data. As an alternative to the cost and complexity of managing on-site SQL Server installations, you’ll learn how to quickly set up and start using database applications in Azure. You’ll gain an understanding of how to configure firewall rules, manage log-ins and users, as well as roles and permissions, perform a database restore, and generally secure an Azure SQL database.

Ongoing monitoring of your database applications is essential so you’ll be introduced to tools and techniques that will help you determine usage requirements, plan upgrades, and troubleshoot performance and security issues.

Finally, you’ll be introduced to Azure SQL Data Warehouse, a fully managed and scalable cloud service, that is compatible with other Azure offerings, such as Machine Learning and Data Factory, as well as existing SQL Server tools. As a distributed database management system that can handle large amounts of data in which analytics play a significant role, Azure SQL Data Warehouse provides an ideal solution for organizations that work with Big Data and need to scale up and down quickly.

课程大纲

  • How to plan for, deploy, and provision Azure SQL Database.
  • How to implement, secure, and manage Azure SQL Database.
  • How to use metrics, alerts, auditing, and dynamic management views to monitor Azure SQL Database.
  • How to use Azure SQL Data Warehouse for Big Data solutions.

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课程简介

Learn how to deploy relational and non-relational databases in the cloud and explore the breadth of Azure’s data services, from a single database instance to a massive scale data warehouse for working with Big Data.

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