In this article, we will explore how to analyze data stored in Amazon S3 using AWS Glue and Athena. We will start by creating an AWS Glue database and table in Athena, and then move on to optimizing our Athena queries using buckets and partitions. Additionally, we will learn how to utilize Athena views and create named queries using CloudFormation.
Next, we will dive into managing data with Amazon S3. We will walk through the process of creating a CloudFormation stack, uploading data to an S3 bucket, and querying data using S3 Select. We will also cover modifying encryption and storage properties, compressing datasets, and testing restricted access for team members.
To further enhance our data management capabilities, we will explore AWS Glue in more detail. We will learn how to configure AWS Glue crawlers to automatically discover and catalog data, and then using Athena to query these tables. Additionally, we will explore how to create CloudFormation templates for AWS Glue crawlers, making it easier to manage and automate our data processing workflows.
By the end of this article, you will have a solid understanding of how to use AWS Glue, Athena, and S3 to analyze and manage your data in Amazon Web Services.

Collections

Explore how to analyze and manage data stored in Amazon S3 using AWS Glue, Athena, and S3. Learn optimization techniques, data querying, and automation with CloudFormation templates.

Amazon Web Services for Dummies: Analyzing Data with AWS Glue, Athena, and S3