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所在平台: Udemy |
课程主页: https://www.udemy.com/course/snowflake-database-querying-data-part-1/
课程评论：没有评论
课程名称：Snowflake数据库 - 查询数据第一部分 课程概述：SQL是全球使用最广泛的查询语言，而Snowflake正在迅速成为最受欢迎的云数据平台。虽然还有其他用于不同类型数据库的查询语言，如NoSQL数据库，但SQL仍然是标准，Snowflake的SQL实现完全符合ANSI标准。Snowflake的云数据平台采用数据仓库/数据湖架构，支持最常用的ANSI标准SQL，能够进行强大的关系数据库查询。Snowflake还可以作为数据湖的替代品或补充，因其能够聚合JSON和Parquet等半结构化数据与结构化数据。该平台简化了对JSON数据的访问，并允许用户将此类数据与结构化数据相结合。 在本课程中，我们将涵盖多种查询技术，比如窗口函数、公共表表达式（CTE）、连接查询、数据生成、时间旅行查询、日期和时间处理、数据透视与反透视查询、正则表达式查询等多种查询类型。我们还将演示如何进行查询性能监控，并重点展示如何使用Snowflake查询半结构化数据，如JSON和Parquet文件。完成本课程第一部分后，您将为执行多种类型的Snowflake查询打下坚实基础。
SQL is the most used query language in the world and Snowflake is quickly becoming the most used cloud data platform in the world. There are, of course, other query languages for different types of databases, such as NoSQL databases but SQL remain the standard and Snowflake's SQL implementation is full ANSI SQL compliant.Snowflake's cloud data platform features a data warehouse / data lake architecture that supports the most common standardized version of SQL (ANSI) for extremely powerful relational database querying. Snowflake can also be used as a data lake replacement, or supplement, because it can also aggregate semi-structured data such as JSON and Parquet, with structured data in a SQL format. Snowflake simplifies access to JSON data and allows users to combine it with structured data. In this course we cover many query techniques such as Windowing functions, Common Table Expressions (CTEs) and Connect By, generating data, time travel queries, working with dates and times, pivot and unpivot queries, regular expression queries and many other types of queries.We demonstrate how to perform query performance monitoring. We also spend a significant amount of time demonstrating how Snowflake can be used to query semi-structured data such as JSON and Parquet files.When you finish part 1 of this course you will have a solid foundation for performing numerous types of Snowflake queries.
