Analyzing Data on AWS

by Clarke Bishop

Studying for the Amazon Certified Data Analytics - Specialty exam, or need to do Big Data Analytics on AWS? In this course, you’ll learn four Amazon Analytics services—specifically Redshift, Elasticsearch, Kinesis Data Analytics, and Athena. 

What you'll learn

Amazon offers four powerful services for data analytics. Only, there’s a lot you need to know to use them effectively.

In this course, Analyzing Data on AWS, you’ll learn to configure and use Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift.

First, you’ll learn how to analyze streaming log files or other text data with Elasticsearch and how to visualize the data with Kibana. Next, you’ll discover how to directly query data in S3 using Amazon Athena along with the Glue Data Catalog and Glue crawlers. Then, you’ll explore SQL queries on real time streaming data with Kinesis Data Analytics. Finally, you’ll learn how to design and use Amazon’s data warehouse—Redshift.

When you’re finished with this course, you’ll have learned key topics covered by the Amazon Data Analytics - Specialty exam, and be ready to create your own data analytics projects on AWS.

Course FAQ

What is the AWS Certified Data Analytics - Specialty Certification?

This certification from Amazon Web Services validates that you're an expert in AWS data lakes and analytics products.

Who is this course for?

This course is ideal for anyone preparing for the AWS Certified Data Analytics - Specialty Certification, or who would like to create their own data analytics projects on AWS.

What will I learn in this course?

In this course, Analyzing Data on AWS, you’ll learn to configure and use Amazon Elasticsearch, Amazon Athena, Kinesis Data Analytics, and Amazon Redshift - key topics covered in the Amazon Data Analytics - Specialty exam.

What prerequisites do I need?

As long as you already know some SQL and have some skills with Amazon's cloud, you're ready for this course.

About the author

Clarke Bishop is a Cloud Architect and Data Engineer who loves solving tough problems. He's worked in Manufacturing, Agriculture, Telecommunications, Construction, Insurance, Financial Services, Human Resources, Marketing, and Media. Skills include Big Data with Spark and Python, Cloud Architecture and Full Stack Web Application Development with JavaScript frameworks and HTML. Clarke has an MBA with a concentration in Finance, a Masters in Electrical Engineering, and a Bachelors in Electrical En... more

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