Data management is a key part of the infrastructure of most organizations, especially those dealing with large data stores. For example, imagine a team involved in scientifical analysis of data: they probably require a system to store the raw data in, another to analyze chunks of data quickly and cost-efficiently, and long-term archival to keep both the raw data and the result of their computation. In cases like that, it's important to deploy an automated system that can move data efficiently with integrated automatic backups.

In this course, the experienced System Administrator and Cloud Expert David Clinton will talk about implementing such a data management and backup system using EBS, S3 and Glacier, and taking advantage of the S3 LifeCycle feature and of DataPipiline for the automation of data transfers among the various pieces of the infrastructure. This system can be enabled easily and cheaply, as is shown in the last lecture of the course.

Who should take this course

As a beginner-to-intermediate course, some basic knoweldge of AWS is expected. A basic knowledge of programming is also needed to follow along the Glacier lecture. In any case, even those who are totally newcomers to these topics should be able to grasp at least the key concepts.

If you want to learn more about the AWS solutions discussed in this course, you might want to check our other AWS courses. Also, if you want to test your knowledge on the basic topics covered in this course, we strongly suggest to take our AWS questions. You will learn more about every single services cited in this course.

If you have thoughts or suggestions for this course, please contact Cloud Academy at support@cloudacademy.com.