Fivetran Bootcamp: Zero to Mastery 2024

所在平台: Udemy

课程主页: https://www.udemy.com/course/fivetran-bootcamp-zero-to-mastery-2022/

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课程简介

## Fivetran Bootcamp: Zero to Mastery 2024 - 课程总结 本课程旨在教授 **Fivetran**,一款强大的数据集成工具,帮助您从各种分散的数据源提取数据并加载到您的数据仓库中。通过本课程,您将掌握 Fivetran 的核心概念和实际应用,为数据工程领域的职业发展打下坚实基础。 **课程亮点:** * **精准高效:** 内容精炼,直击要点,不浪费时间。 * **实战导向:** 强调实时实践和动手操作,帮助您真正掌握技能。 * **面试加分项:** 学习到的经验和技能将有助于您在面试和工作讨论中脱颖而出。 * **行业最佳实践:** 涵盖复杂的架构解决方案,并融入行业领先的最佳实践。 * **Fivetran 最佳实践:** 专门介绍使用 Fivetran 的有效方法。 **基础要求:** * 对 ETL(提取、转换、加载)有基本了解(非必需)。 * 具备基础 SQL 知识(非必需)。 * 课程将涵盖所有必要的入门知识。 **课程内容概览:** * **数据管道基础:** 了解什么是数据管道及 ETL 的核心概念,探讨传统 ETL 方法面临的挑战。 * **Fivetran 详解:** * 什么是 Fivetran 及其优势。 * 如何创建 Fivetran 免费账户。 * Fivetran 的不同计划和账户类型。 * 数据目标(Destinations)的类型,包括托管目的地(Managed Destinations)。 * 设置 Snowflake 和 Redshift 的免费试用账户及配置为 Fivetran 目标。 * Fivetran 与 DBT (Data Build Tool) 的集成与设置。 * **数据转换:** 学习什么是数据转换,以及 Fivetran 数据转换的功能。 * **Fivetran 架构:** 深入理解 Fivetran 的整体架构。 * **账户管理:** 了解 Fivetran 的账户管理概览。 * **实际操作流程:** * Fivetran 如何帮助您集中管理分散的数据源。 * 从浏览器端操作实现数据提取和加载。 * 从连接数据仓库到添加数据连接器(Connectors)的完整流程。 * 初次设置所需时间(5 分钟至 2 小时,取决于防火墙和集成设置)。 * 添加新连接器的配置和验证过程。 * 连接器创建后数据的即时同步和使用。 * 根据需求添加多个连接器。 **适合人群:** * **数据工程专业人士:** 希望提升或掌握 Fivetran 工具的专业人士。 * **大学应届毕业生:** 寻求进入数据工程领域的学生。 * **IT 开发者:** 希望从其他技术领域转向数据工程领域的开发者。 * **数据工程师/数据仓库开发者:** 正在使用本地(on-premises)技术或其他云平台(如 AWS, GCP)的用户,希望学习 Azure 相关技术。 * **数据架构师:** 希望了解基于云的 ETL 工具的架构师。 * **数据科学家:** 想要扩展知识边界,涉足数据工程领域的数据科学家。 本课程将为您提供一个清晰、直接的学习路径,帮助您快速掌握 Fivetran,并在数据工程领域迈出坚实的一步。

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课程详情

RequirementsBasic understanding about ETL and Basic SQL will be useful, but not necessary.I will take you through everything necessary to learn this course.DescriptionWelcome to Fivetran Bootcamp! Fivetran helps you centralize data from disparate sources which you can manage directly from your browser. In this course you will learn to extract your data and load it into your data destination. This course will help you in preparing and mastering your Fivetran ETL tool concepts.Highlights of the Course:Designed to keep only précised information no beating around the bush. Real-time implementation, learn with Practical.It will help you to showcase your experience in interviews and discussions.Involve complex architecture solution which is aligned with industry best practices.Added the Best Practices to be used with FivetranTopics Covered in the Course:What is a data pipelineWhat is ETLChallenges in the traditional ETLwhat is FivetranCreate A Free AccountFivetran plansFivetran types of destinationsTypes of Accounts and Create Managed destinationCreate Snowflake Free Trial AccountCreate Redshift Clusterset up Redshift destinationset up snowflake destinationFivetran and DBT set upwhat is TransformationFivetran Data TransformationsFivetran AcrhitectureFivetran: Account Management OverviewFivetran helps you centralize data from disparate sources which you can manage directly from your browser. We extract your data and load it into your data destination. If you already have an account, setup takes anywhere from 5 minutes to 2 hours (depending on the complexity of your internal firewalls and integration setups). The first step is to connect a data warehouse. After that, you'll be taken to the Dashboard, where you can add new connectors. Adding a new connector will lead you to the setup page with detailed notes on the screen and verification for the configuration. Once your first connector is created, it will begin syncing immediately and once that is done you can start using that data in your data warehouse. You can add as many connectors as needed to complete your initial setup.Who this course is for:Data engineering ProfessionalsUniversity students looking for a career in Data EngineeringIT developers working on other disciplines trying to move to Data EngineeringData Engineers/ Data Warehouse Developers currently working on on-premises technologies, or other cloud platforms such as AWS or GCP who want to learn Azure TechnologiesData Architects looking to gain an understanding about cloud based ETL toolData Scientists who want to extend their knowledge into data engineering

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