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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-dbt-bootcamp-transform-your-data-using-data-build-tool/
课程评论：没有评论
课程名称：数据训练营：使用 dbt 转换您的数据 课程概述：您是否在寻找一种前沿的方法来提取、加载和转换您的数据？您是否想了解更多关于 dbt™ 及其使用方法的信息？那么，这门课程正适合您。欢迎来到 dbt™ 训练营：使用 dbt™ 转换您的数据。在本课程中，您将全面了解 dbt™，从设置 dbt™ Cloud、将其连接到 Snowflake 或您选择的数据仓库、开发模型、创建数据源、进行测试、使用文档到更多其他内容。本课程适合初学者，我们将通过一个现实项目，实用地涵盖上述每一个步骤。 dbt™ 是一个数据建模工具，使分析师和工程师的工作变得更加简单。它允许您编写 SQL 查询，而无需担心依赖关系。dbt™ 基于 SQL，但在其上构建了额外的功能，利用模板引擎如 JINJA。这使您能够使用额外的逻辑检索、重新排列和组织数据。然后，您可以使用 dbt™ 的运行命令编译和运行这些代码，以检索在转换过程中所需的部分。此外，它能够快速编码、测试和调整，而无需等待处理所有数据，其自动化文档功能也节省了大量时间。 我们将进行的项目是关于一个虚构公司 GlobalMart。GlobalMart 销售家具、办公设备、家用电器和电子产品。他们正在招聘一个小型数据团队，并希望尝试使用 dbt™ 进行数据转换。他们需要一些关于利润的报告表，希望使用 dbt™ 转换数据来实现这些需求。 在本课程结束时，我们将完成以下任务： 1. 设置 dbt™ Cloud 帐户 2. 连接到数据库（本实例使用 Snowflake） 3. 将 dbt™ 连接到 GitHub 等代码库 4. 理解 dbt™ Cloud 界面 5. 在 dbt™ 中构建和运行模型 6. 在 dbt™ 中使用模块化 7. 创建和引用数据源 8. 在 dbt™ 中执行测试，包括单一测试和通用测试 9. 如何在 dbt™ 中创建和生成文档 10. 如何在 dbt™ 中进行部署 11. 如何使用 Jinja 12. 在 dbt™ 中使用宏和包 13. 使用 Seeds 和 Analyses 这是一门极具全面性的课程，将真正提升您在 dbt 方面的技能，以及在提取、加载和转换过程中的能力。感谢您选择这门课程，期待在下节课见到您。
Are you looking for a cutting-edge way to extract load and transform your data? Do you want to know more about dbt™ and how to use it? Well, this is the course for you. Welcome to The dbt™ Bootcamp: Transform your Data using dbt™.In this course you are going to learn all about dbt™, from setting up dbt™ cloud, connecting it to Snowflake or a warehouse of your choice, developing models, creating sources, doing testing, working with the documentation and much more. This course is for beginners, we will go through a realistic project and cover each of the steps mentioned in a practical approach.dbt™ is a data modelling tool that makes life much easier for analysts and engineers. It allows you to write SQL queries without having to worry about dependencies. dbt™, like traditional databases, is built on SQL, but it has additional functionality built on top of it utilizing templating engines such as JINJA. This effectively lets you to retrieve, rearrange, and organize your data using additional logic in your SQL. You may then compile and run this code using dbt's™ run command to retrieve just the pieces you need in the transformations. It can also be swiftly coded, tested, and adjusted without having to wait for it to process all your data. In addition to that, it's automated documentation is a big time saver.The project we will be working on is about a fictitious company called GlobalMart. GlobalMart sells household items like furniture, office equipment, Appliances and Electronics. They are in the process of hiring a small data team and would like to try out dbt™ for their data transformations. They require some reporting tables about their profits and want to use dbt™ to transform their data to get them what they want.By the end of this course, we will work through the project and end up accomplishing the following:1. Setting up a dbt™ Cloud Account2. Connecting to a Database (in this case Snowflake)3. Connecting dbt™ to a repository like GitHub4. Understanding the dbt™ cloud interface5. Building and Running Models in dbt™6. Using Modularity in dbt™7. Creating and Referencing Sources8. Performing Tests in dbt™ including Singular and Generic Tests9. How to Create and Generate Documentation in dbt™10. How to Deploy in dbt™11. How to use Jinja12. Using Macros and Packages in dbt™13. Using Seeds and Analyses in dbt™This is a great, comprehensive which will really up-skill you not only in dbt but the extract, load and transform process as well.Thank you so much for choosing this course and I'll see you in the next lecture.
