Data Analytics and Databases on AWS

Amazon Web Services via Coursera

Go to Course: https://www.coursera.org/learn/data-analytics-and-databases-aws

Introduction

Key data types and structures

AWS services for the ETL process

Hands-on skills for Amazon API Gateway and Amazon QuickSight

Syllabus

Module 1: Foundations of Data Analysis

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).

Module 2: ETL Pipeline and Database Foundations

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.

Module 3: AWS Services for ETL

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.