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Analyzing Data with Amazon Athena

Contents

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Amazon Athena - In-depth Review

The course is part of this learning path

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Amazon Athena - Introduction
Overview
DifficultyIntermediate
Duration32m
Students1248
Ratings
5/5
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Description

In this course, 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 course, 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 course 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 course, you should have an understanding of big data and analytical concepts, the Amazon Simple Storage Service, and SQL.

Transcript

Hello and welcome to the Cloud Academy course on Amazon Athena. Before we start I'd like to introduce myself. My name is Jeremy Cook. I'm one of the trainers here at Cloud Academy specializing in AWS. Feel free to connect with either myself or the wider team here at Cloud Academy regarding anything about this course. You can email us at support@cloudacademy.com. Alternatively our online community forum is available for your feedback.

In this training course you'll be introduced to Amazon Athena. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Let's quickly review the Amazon Athena offering. It allows you to quickly query unstructured, semi-structured, and structured data stored in S3. It's a server-less based service. You only pay for the data scanned. Built on Presto technology and open source distributed SQL query engine. Provides and SQL like dialect for data querying. Designed to provide fast performance for large data set scanning. The agenda for the remainder of this course is as follows. We'll review and explain fundamental AWS Athena storage and querying concepts. We'll highlight suitable use cases in which Athena can be applied effectively. We'll review the basic underlying technology that Athena has been built on. We'll discuss and illustrate the process of creating and setting up Athena tables, formats, and partitions. We'll examine the process in which Athena SQL queries are offered. We'll review current Athena limitations and pricing. Finally we'll 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. Finally, we'll use Athena to search and find the captured security group API update calls. The following prerequisites will be both useful and helpful for this course. General big data and analytical concepts; Amazon Simple Storage Service, S3; SQL, Structured Query Language. Furthermore if you require an introduction to S3 then please consider taking the free S3 lab hosted here on Cloud Academy.

About the Author
Students36337
Labs33
Courses93
Learning paths23

Jeremy is the DevOps Content Lead at Cloud Academy where he specializes in developing technical training documentation for DevOps.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 20+ years. In recent times, Jeremy has been focused on DevOps, Cloud, Security, and Machine Learning.

Jeremy holds professional certifications for both the AWS and GCP cloud platforms.