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所在平台: Udemy |
课程主页: https://www.udemy.com/course/fivertran/
课程评论：没有评论
课程名称：从零开始构建 Fivetran ETL 课程概述： 本课程深入介绍了 Fivetran ETL 的核心概念和运作方式。课程将数据组织的基本组成部分——表（tables）和模式（schemas）——进行了类比，将表比作按行和列组织的文档，而模式则被看作是包含多个表的文件夹。 课程重点阐述了 Fivetran 连接器（connectors）的作用： * **连接与提取（Extract）：** 每个 Fivetran 连接器负责创建一个并管理自己的模式。它会主动连接到数据源，接收数据，然后将其写入目标数据库。根据连接器类型的不同，Fivetran 要么接收源系统主动推送的数据，要么主动向源系统发送请求并接收响应中包含的数据。 * **加载（Load）：** Fivetran 的核心职责是确保将最新的、准确的数据以一种清理和规范化的模式（即规范模式，canonical schema）加载到目标系统，并且保证数据达到最小的聚合级别。 * **维护与演进：** Fivetran 负责定期维护连接器，并根据源系统操作和产品变更来演进其规范模式。同时，Fivetran 也会积极响应任何源系统操作上发生的未知中断性变更，确保从源系统到目标模式的抽取和加载过程的顺畅。 课程还说明了 Fivetran 的整体架构： * Fivetran 能够连接到所有支持的数据源，并将数据从中加载到用户指定的目标数据库中。 * 每个数据源对应着一个或多个连接器，这些连接器作为独立的进程运行，并在单次更新期间持续存在。 * 一个 Fivetran 账户可以包含多个连接器，从而实现从多个数据源向一个或多个目标数据库加载数据的能力。
The building blocks of data organization are tables and schemas. You can think of a table as a file organized by rows and columns and of a schema as a folder that contains multiple tables. Each Fivetran connector creates and manages its own schema. Fivetran connector reaches out to your source, receives data from it, and writes it to your destination. Depending on the type of connector, Fivetran either collects data that the source pushes to us or sends a request to the source and then grabs the data that the source sends in response.Fivetran's responsibilityIt is Fivetran's responsibility to deliver up-to-date, accurate information in a cleaned and normalized schema - the canonical schema - at the lowest level of aggregation. It is our responsibility to regularly maintain the connector and evolve the canonical schema to reflect operational and product changes in the source systems. It is our responsibility to respond to any unknown operational breaking change in the extract and load from the source system to the destination schema.Fivetran connects to all of your supported data sources and loads the data from them into your destination. Each data source has one or more connectors that run as independent processes that persist for the duration of one update. A single Fivetran account, made up of multiple connectors, loads data from multiple data sources into one or more destinations.
