Chris Kimmel
成为会员时间:2022
成为会员时间:2022
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
“Google Cloud 基础知识:核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务,并提供重要的资源和政策管理工具。
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
各种规模的组织都在利用云的强大功能和灵活性来改变运营方式。然而,有效管理和扩缩云资源可能是一项复杂的任务。本课程探讨了云中现代运营、可靠性和弹性方面的基本概念,以及 Google Cloud 如何帮助支持这些工作。 作为 Cloud Digital Leader 学习路线的一部分,本课程旨在帮助个人在自己的岗位上成长,并为企业谋求未来发展。
许多传统企业都在使用无法满足现代客户期望的旧式系统和应用。业务领导者往往需要在维护老旧的 IT 系统和投资新产品与服务之间做出选择。本课程探讨了这些挑战,并提供了利用云技术克服这些挑战的解决方案。 作为 Cloud Digital Leader 学习路线的一部分,本课程旨在帮助个人在工作中成长,并为企业打造美好未来。
云技术是一项强大的资产,与数据相结合后,它将成为创新和提升客户体验的催化剂。《使用 Google Cloud 探索数据转换》课程探讨了组织如何利用云技术让数据更易于访问、更具实用价值和商业价值。 作为“Cloud Digital Leader 学习路线”的一部分,本课程旨在帮助个人提升职业素养,并为企业谋求未来发展。
数字化转型是现代组织的必经之路,而扎实掌握云计算基础知识,是推动实质性创新的第一步。《利用 Google Cloud 实现数字化转型》课程将讲解核心技术与战略框架,助力组织实现运营现代化。本课程介绍关于云的基本概念、全球网络基础设施和责任共担模式,帮助领导者从容推进上云进程。 作为 Cloud Digital Leader 学习路线的一部分,本课程旨在帮助学员提升岗位能力,从而为企业打造美好未来。