AWS Data Analytics
AWS Tutorial: AWS Data Analytics
Welcome to the AWS Data Analytics lesson. Storing massive amounts of data is cheap in the cloud, but that data is useless unless you can extract actionable business insights from it.
Why Learn AWS Analytics?
"Data is the new oil." Companies rely on Big Data analytics to understand customer behavior, forecast sales, and optimize logistics. Knowing which AWS analytics tool to use is a highly sought-after skill for Cloud Architects and Data Engineers.
Tutorial Overview
In this tutorial, you will learn about the primary analytics services in AWS:
- Amazon Athena: Serverless SQL queries.
- Amazon EMR: Big Data processing.
- Amazon QuickSight: Business Intelligence (BI) dashboards.
The Analytics Ecosystem
- Amazon Athena: An interactive, serverless query service that makes it easy to analyze massive datasets directly in Amazon S3 using standard SQL. You don't have to load the data into a database first; you just point Athena at your S3 bucket and run the query! You pay only for the queries you run.
- Amazon EMR (Elastic MapReduce): A cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and machine learning applications using open-source analytics frameworks like Apache Spark, Apache Hive, and Presto.
- Amazon QuickSight: A fully managed Business Intelligence (BI) and data visualization service. It connects to your databases or Athena, allowing you to create interactive dashboards, graphs, and reports to share with business executives.
Exercise
?Which serverless AWS service allows you to run standard SQL queries directly against raw files stored in an Amazon S3 bucket?