Analyzing Data with Amazon Athena

Intermediate
2m 32s
4,267
4.7/5

Please note: this lesson has been removed from our training library and replaced with a new one here: Analyzing Data With Amazon Athena

 

In this lesson, we will perform an in-depth review of the Amazon Athena service. We will review and explain fundamental AWS Athena storage and querying concepts, highlighting the suitable use cases in which Athena can be applied effectively.

You will be introduced to the basic underlying technology that Athena has been built on, and we spend time discussing the process of creating and setting up Athena databases, tables, and partitions. We examine the process in which Athena SQL queries are authored and how they are managed. We review current Athena limitations and pricing.

Finally, we will provide a demonstration in which we publish CloudTrail logs into an S3 bucket. We'll make some ad-hoc security group changes to generate a few CloudTrail events before finally using Athena to search and find the captured security group API update calls.

If you have any feedback relating to this lesson, feel free to contact us support@cloudacademy.com.

Learning Objectives

  • Get a basic understanding of Amazon Athena and the process of creating Athena databases, tables, and partitions
  • Manage and author Athena SQL queries
  • Understand the pricing and limitations of Athena
  • Publish and query CloudTrail logs using Athena SQL queries

Intended Audience

This lesson is intended for IT professionals or anyone interested in using the Amazon Athena service for their data storage needs.

Prerequisites

To get the most out of this lesson, you should have an understanding of big data and analytical concepts, the Amazon Simple Storage Service, and SQL.

About the Author
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Jeremy Cook, opens in a new tab
Content Lead Architect
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Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).

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