微软 DevOps 应用
Introduction:
An export-based startup is trying to move to the cloud. They have selected Microsoft Azure cloud for their cloud service provider. They have an on-premises database that they would like to move to Azure cloud. They have already downloaded the data in the form of a .csv file. This file is available in the wiki section of Azure DevOps. The cloud database they want to use is SQL Database on Azure. They would like all their offline data in the cloud database by the end of this project The database contains PII data (know more about what constitutes PII data here) which means we need to handle the data carefully. Remember, for the purpose of this project the data that we are using is fake however in real-life PII data is governed by regulations. The customer is open to ideas (I’m the customer, so you can discuss with me the options) however they want to use Azure Data Factory to transfer the data from .csv file to the cloud database. A single data pipeline is enough as far as the customer is concerned. This pipeline can be run manually (no automation required).
Task:
Sprint 1 is already complete. The task was to sign up for Azure DevOps which you did in Week one.
Define formal requirements from the description above. If you have any questions, you can send me an email. This would be requirement gathering and this the task for Sprint 2. Once you are sure about the requirements, you will put them down in a document (1 page max) formally in Sprint 3. In Sprint 4 & 5, you will implement the solution using your student Subscription of Microsoft Azure. During Sprint 5 you will also present your solution using a Zoom meeting.
Azure DevOps:
Go to Azure DevOps à Boards à Sprints. Here you will see all the tasks that need to be performed. You have already been assigned to the task however its status is not set. Once you start working on a task, change its status to “Doing” and once you are done, change its status to “Done”. These tasks are placed in sprints. Each sprint lasts for a week and task must be completed within the week.
会使用微软DevOps和SQL的来，详细信息加我微信X_GeQAQ，另有酬。
大概步骤：
ADF(Azure Data Factory)中创建数据工厂。
ADF(Azure Data Factory)中 创建包含复制活动的管道。
ADF(Azure Data Factory)中 测试性运行管道。
ADF(Azure Data Factory)中 手动触发管道。
ADF(Azure Data Factory)中 按计划触发管道。
ADF(Azure Data Factory)中 监视管道和活动运行。
望采纳，告知详情
需要通过SQL完成什么。
DevOps（英文Development和Operations的组合）是一组过程、方法与系统的统称，用于促进开发（应用程序/软件工程）、技术运营和质量保障（QA）部门之间的沟通、协作与整合。它的出现是由于软件行业日益清晰地认识到：为了按时交付软件产品和服务，开发和运营工作必须紧密合作。
这只是介绍吧,你想问什么问题.
引言：
一家以出口为基础的初创公司正试图向云技术发展。他们已选择Microsoft Azure cloud作为其云服务提供商。他们有一个内部数据库，他们希望将其移动到Azure云。他们已经以.csv文件的形式下载了数据。此文件位于Azure DevOps的wiki部分。他们想要使用的云数据库是Azure上的SQL数据库。他们希望在本项目结束时，他们的所有离线数据都在云数据库中。该数据库包含PII数据（了解更多关于PII数据的构成信息），这意味着我们需要仔细处理数据。请记住，在本项目中，我们使用的数据是虚假的，但在现实生活中，PII数据受法规管辖。客户对想法持开放态度（我是客户，因此您可以与我讨论选项），但他们希望使用Azure Data Factory将数据从.csv文件传输到云数据库。就客户而言，单个数据管道就足够了。该管道可以手动运行（无需自动化）。
任务：
Sprint 1已经完成。任务是注册Azure DevOps，这是您在第一周完成的。
根据上述描述定义正式需求。如果你有任何问题，可以给我发电子邮件。这将是需求收集，这是Sprint 2的任务。一旦您确定了需求，您将在Sprint 3中正式将其放在文档中（最多1页）。在Sprint 4和5中，您将使用学生订阅的Microsoft Azure实现解决方案。在Sprint 5中，您还将使用Zoom会议展示您的解决方案。
Azure DevOps：
转到Azure DevOpsáBoardsáSprint。在这里，您将看到需要执行的所有任务。您已被分配到该任务，但其状态尚未设置。一旦你开始处理一项任务，将其状态更改为“正在进行”，一旦你完成了，将其状况更改为“已完成”。这些任务放在sprint中。每次冲刺持续一周，任务必须在一周内完成。
这是想做什么呢？DevOps（Development和Operations的组合词），貌似最近比较火的一个概念。