Data Analytics and Databases on AWS
Amazon Web Services
In this course, you develop essential skills that will help you think like a data analyst. You explore key data types and structures, and apply this knowledge directly to discussions on SQL and NoSQL databases. The course also places significant emphasis on the extract, transform, and load (ETL) process. Through each step, you gain insights into handling data, ensuring data quality, managing databases effectively, and integrating data seamlessly. Additionally, you learn about essential AWS se...
About this Course
This course starts by introducing fundamental concepts in data analysis. You begin with how to assess use cases for data analysis in the cloud. After exploring some of the main data types and structures, you’ll complete the module by contrasting two data-processing approaches for analytics: extract, transform, and load (ETL) and extract, load, and transform (ELT). You’ll then transition to start learning about the ETL pipeline, 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.
What You'll Learn
- Key data types and structures
- Foundations of SQL and NoSQL databases
- Common SQL queries
- ETL steps for data processing
- AWS services for the ETL process
- Hands-on skills for Amazon API Gateway, Amazon Relational Database Service (Amazon RDS), and Amazon QuickSight
Instructors
Oksana Hoeckele
Cloud Technologist
Rafael Lopes
Senior Cloud Technologist