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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-engineering-snowflake
课程评论：没有评论
课程名称：现代数据工程导论（使用Snowflake） 课程概述：这个技术导向的实践课程教会学习者如何使用Snowflake构建现代、持续的数据管道。课程专注于最实用的Snowflake概念和工具，帮助学习者快速上手数据管道的构建。 在课程开始时，学习者将了解现代数据工程的“数据摄取-转化-交付”（Ingestion-Transformation-Delivery，简称ITD）框架，深入学习框架中的每个组成部分，包括： 1. **数据摄取与Snowflake**： 学习者将学习如何以规模化的方式将数据摄取到Snowflake，通过多种强大技术加载数据，包括Snowflake市场、Snowsite、Snowflake命令行接口（CLI）以及COPY INTO SQL命令。他们还将了解到如何利用Snowflake的原生连接器从外部系统摄取数据，并通过充分利用虚拟仓库来优化数据摄取。 2. **数据转化**： 学习者将使用SQL或Snowpark for Python进行数据转化，并了解到如何使用Snowpark进行Java和Scala的数据转化。他们将扩展对数据转化的知识，学习创建和使用用户定义函数（UDF）、存储过程、流和Snowflake动态表。在此过程中，学习者还将在Visual Studio Code中使用Snowflake的官方扩展进行数据转化。 3. **数据产品的交付**： 学习者将理解数据管道中的编排（orchestration）概念，学习如何通过任务将自动化添加到数据管道中。他们特别会学习用户管理的任务和无服务器任务，创建任务以自动调用存储过程，并相互链接任务形成任务图（DAG），执行单个任务及整个DAG。 4. **持续数据管道的编排**： 学习者将进一步深入编排的概念，了解如何通过任务为数据管道添加自动化，创建用户管理和无服务器任务，形成任务图以实现高效的数据流转。 通过该课程，学习者将全面掌握使用Snowflake进行现代数据工程的关键技能，快速构建和维护高效的数据管道。
Name:Modern data engineering with Snowflake
Description:Learners understand how the explosion of data in recent years has led to an increased demand for extracting insights from that data, giving rise to data engineering. They'll understand previous data engineering approaches, modern data engineering approaches using Snowflake, and contextualize data engineering with the Ingestion-Transformation-Delivery ("ITD") framework. They also prepare their development environment and build a simple data pipeline with Snowflake.
Name:Batch data ingestion with Snowflake
Description:Learners learn how to ingest data into Snowflake at scale using various, powerful techniques. They specifically load data into Snowflake using the Snowflake Marketplace, the Snowflake web interface (Snowsight), the Snowflake CLI, and the powerful COPY INTO SQL command. Learners also understand how to ingest data from external systems using Snowflake native connectors, and how to optimize data ingestion by fully utilizing a virtual warehouse.
Name:Data transformations with Snowflake
Description:Learners perform data transformations using SQL or Snowpark for Python. Learners also understand that they can use Snowpark to perform data transformations with Java and Scala. They also extend their knowledge of data transformations by learning about, creating, and using user-defined functions (UDFs), stored procedures, streams, and Snowflake Dynamic Tables. They also learn how to perform data transformations using these tools outside of Snowflake, specifically in Visual Studio Code using Snowflake's official extension.
Name:Delivering data products with Snowflake
Description:Learners understand what orchestration means, and how to add automation to data pipelines using tasks. They specifically learn about user-managed and serverless tasks, and create tasks to automate calls to stored procedures. They also create and link tasks together to form a task graph, or DAG, and execute individual tasks and entire DAGs.
Name:Orchestrating continuous data pipelines with Snowflake
Description:Learners understand what orchestration means, and how to add automation to data pipelines using tasks. They specifically learn about user-managed and serverless tasks, and create tasks to automate calls to stored procedures. They also create and link tasks together to form a task graph, or DAG, and execute individual tasks and entire DAGs.
This is a technical, hands-on course that teaches learners how to build modern and continuous data pipelines with Snowflake. It focuses specifically on the most practical Snowflake concepts and tools to get learners up and running quickly with building data pipelines. Learners start by learning about the "Ingestion-Transformation-Delivery" framework for modern data engineering, and dive deeper into each component of the framework by learning how to: - Ingest data into Snowflake at scale using
