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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-management-and-storage-in-the-cloud
课程评论：没有评论
课程名称：云端数据管理与存储 概述：嗨！这是谷歌云数据分析证书的第二门课程。这里将带您了解数据治理的关键组件、规范化和星型模式、数据目录以及数据湖屋架构的基本概念。 课程大纲： 1. **云端数据管理与存储简介** 描述：揭开云端数据组织的奥秘！这个模块将深入探讨数据的不同形式、存储方式以及数据的移动方式（想象一下API和连接器就像你的数据运输巫师）。准备好了解构建良好管理数据系统的基础要素。 2. **数据组织的关键组件** 描述：提升您的数据组织技能！在这个模块中，您将解码数据治理、模式（数据蓝图）及数据湖屋的力量。了解这些概念如何协同工作，创建一个既强大又易于导航的数据系统。 3. **数据查找的步骤** 描述：是时候进行数据寻宝了！在这个模块中，您将利用谷歌云工具，如BigQuery和Dataplex，追踪、访问及存储所需的数据。将其视为解决复杂商业问题的数字侦探工具包。 4. **访问数据的技巧** 描述：成为数据的使者！此模块将教您如何与数据表交流，并超级提升查询速度，以获得快速见解。您将探索基于云的数据湖和数据仓库的力量，从而自信地回答棘手的商业问题。 通过本课程，学员将提升在云端环境中管理和组织数据的能力，掌握数据治理及存储的最新技术，为未来的数据分析奠定坚实基础。
Name:Introduction to data management and storage in the cloud
Description:Unlock the secrets of data organization in the cloud! In this module, you'll dive into the different forms data can take, how to store it, and the magic of moving it around. (Think of APIs and connectors as your data transport wizards!) Get ready to understand the building blocks of a well-managed data system.
Name:Key components of data organization
Description:Level up your data organization skills! In this module, you'll decode the mysteries of data governance, schemas (the blueprints of data), and the power of the data lakehouse. Discover how these concepts work together to create a data system that's both powerful and easy to navigate.
Name:Steps to find data
Description:Time for a data treasure hunt! In this module, you'll use Google Cloud tools, like BigQuery and Dataplex, to track down, access, and store the data you need. Think of it as your digital detective kit for solving those tricky business problems.
Name:Techniques to access data
Description:Become a data whisperer! This module teaches you how to talk to data tables and supercharge your queries for lightning-fast insights. You'll explore the power of cloud-based data lakes and warehouses, so you can answer tough business questions with confidence.
Hi again! This is the second course of the Google Cloud Data Analytics Certificate. Get cozy with the key components of data governance, normalized and star schemas, data catalogs, and data lakehouse architecture.
