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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-analytics-and-databases-aws
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课程名称：AWS上的数据分析与数据库 课程概述：数据无处不在。如果您或您的公司不知道自己拥有哪些数据以及能够通过数据挖掘出什么洞察，您将处于竞争劣势。在本课程中，您将了解数据分析的基本知识以及以数据驱动的决策所带来的优势。您将学习数据在当今世界的普遍存在，以及怎样开始像数据分析师一样思考和行动。第一周的内容将比较ETL（提取、转换、加载）和ELT（提取、加载、转换）这两种数据处理方法。 课程大纲： 1. 模块1：数据分析基础 - 描述：欢迎来到课程的第一个模块。本模块介绍数据分析的基本概念。您将首先评估云端数据分析的用例，然后探索主要的数据类型和结构，并了解元数据如何帮助您管理数据集。最后，您将通过比较ETL和ELT两种数据处理方法来结束本模块。 2. 模块2：ETL管道与数据库基础 - 描述：在本模块中，您将开始学习ETL管道，重点关注真实世界的场景。在每个步骤中，您将学习如何收集数据、确保数据质量、找出合适的存储或数据库，并评估所获得的洞察。在审查ETL流程后，您将评估SQL和NoSQL数据库，并通过动手活动来实践您的技能。 3. 模块3：AWS的ETL服务 - 描述：在本模块中，您将回顾AWS用于数据分析的服务，并通过实操实验来巩固您的学习。这些服务包括Amazon API Gateway、Amazon关系数据库服务（Amazon RDS）、Amazon DynamoDB和Amazon QuickSight。您将在AWS管理控制台中回顾这些服务，并评估如何在ETL过程中使用每项服务。接着，您将通过与这些服务在预配置环境中工作获得实际经验。 通过本课程的学习，您将对数据分析及其在AWS环境中的应用有一个全面的了解，以及如何利用这些工具和技术来获取有价值的数据洞察。
Name:Module 1: Foundations of Data Analysis
Description:Welcome to the first module of the course. This module introduces fundamental concepts in data analysis. You begin the module with how to assess use cases for data analysis in the cloud. Then, you explore some of the main data types and structures, and learn how metadata can help you manage datasets. Lastly, you complete the module by contrasting two data-processing approaches for analytics: extract, transform, and load (ETL) and extract, load, and transform (ELT).
Name:Module 2: ETL Pipeline and Database Foundations
Description:In this module, you start learning about the ETL pipeline, with an emphasis on the real-world scenario. Through each step, you learn how to gather data, ensure data quality, locate the appropriate storage or database, and evaluate insights. After you examine the ETL process, you assess SQL and NoSQL databases, and interact with a hands-on activity to practice your skills.
Name:Module 3: AWS Services for ETL
Description:In this module, you review AWS services for data analysis, and reinforce your learning through practical labs. These services include Amazon API Gateway, Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB, and Amazon QuickSight. You review these services in the AWS Management Console, and evaluate how you can use each service in the ETL process. Then, you gain practical experience by working with some of these service in a preconfigured environment.
Data is everywhere. If you or your company don't know what data you have and what insights you can uncover through your data, you are at a competitive disadvantage. In this course, you'll get introduced to data analytics and the upside of data-driven decisions. You'll learn about the omnipresence of data in today's world and what it takes to start thinking and acting like a data analyst. Week 1 concludes by comparing and contrasting ETL (Extract, Transform, Load) and ELT(Extract, Load, Transform
