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所在平台: Udemy |
课程主页: https://www.udemy.com/course/snowflake-python-applications/
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课程名称：在Snowflake中部署Python应用程序实践 课程概述：该课程将通过一个简单的ETL/ELT的Python/SQL代码，展示如何以多种方式在Snowflake中或与Snowflake连接部署应用程序。每种部署方式都会详细描述系统架构及其对可扩展性、数据保护和安全性的影响，以及代码运行与数据的距离。 适合人群： - 希望扩展Snowflake知识的Python开发者 - 针对Snowflake的未来数据架构师 - 想要理解各种Snowflake应用开发的解决方案架构师 - 想要进入数据架构领域的数据工程师 - 任何希望更好理解Snowflake AI数据云中各种架构的技术人员 您将学习到： - 如何以多种方式将应用程序正确部署到Snowflake AI数据云中 - 如何在Python中实现简单的业务逻辑，并通过Snowflake SQL引擎执行代码 - 如何将简单的Streamlit本地Web应用程序转变为在Snowflake容器中运行的复杂原生应用程序 - 在构建和部署数据应用程序时，如何从系统架构、模块化和可扩展性的角度进行思考 - 如何可视化数据应用程序的不同构建模块 - 如何使用Snowflake内置函数或Python库生成假数据 将介绍的架构包括： - SQL工作表和Python工作表 - Python的Snowflake连接器 - Snowpark数据框API和用于存储过程的Snowpark - Pandas数据框API - 使用Python的存储过程和以调用者身份执行 - Jupyter笔记本和Snowflake笔记本 - Streamlit Web应用程序和Streamlit社区云 - 在Snowflake应用程序中使用Streamlit - 安全数据共享 - Snowflake原生应用 - Snowpark容器服务 - 用于Snowflake和Jupyter的VSCode扩展 通过本课程的学习，您将能够深入了解Snowflake环境下应用程序的部署与架构设计。
This course will take one simple ETL/ELT piece of Python/SQL code and deploy it in over a dozen different ways, in Snowflake or connected to Snowflake. Each time describing the system architecture and the implications. On scalability, data protection and security, how close to the data the code runs.Who this course is forPython developers looking to extend their knowledge of Snowflake.Aspiring Data Architects, with focus on Snowflake.Solution Architects with a goal of understanding all sorts of Snowflake application development.Data Engineers looking to move into Data Architecture.Any technical person willing to better understand all sorts of architectures in Snowflake AI Data Cloud.What you will learnHow to properly deploy an application into the Snowflake AI Data Cloud in multiple ways.How to implement simple business logic in Python and get the code executed by the Snowflake SQL engine.How to get from a simple Streamlit local web app to a complex Native App running in Snowflake Containers.How to think in terms of system architecture, modularity and scalability, when building and deploying a data application.How to visualize the different building blocks of a data application.How to generate fake data with either built-in Snowflake functions or Python libraries.What kind of architectures we'll present hereSQL Worksheets and Python WorksheetsSnowflake Connector for PythonSnowpark DataFrame API and Snowpark for stored procsPandas DataFrame APIStored Procedures in Python and Execute as CallerJupyter Notebooks and Snowflake NotebooksStreamlit Web Apps and Streamlit Community CloudStreamlit in Snowflake ApplicationsSecure Data SharingSnowflake Native AppsSnowpark Container ServicesVSCode Extensions for Snowflake and Jupyter
