Processing Data on AWS
By Dan Tofan
Course info
Course info
Description
Learning the fundamentals of data processing with AWS is not as difficult as it may seem. In this course, Processing Data on AWS, you will learn how to process large amounts of data on AWS. First, you’ll explore data processing with Lambda and Glue. Next, you’ll discover the basics of the Hadoop ecosystem and how to use it with AWS EMR. Finally, you’ll learn how to automate data processing using AWS Data Pipeline. When you’re finished with this course, you’ll have the skills and knowledge of the AWS services needed to process large amounts of data on AWS and get certified in it.
About the author
As a software engineer and lifelong learner, Dan wrote a PhD thesis and many highly-cited publications on decision making and knowledge acquisition in software architecture. Dan used Microsoft technologies for many years, but moved gradually to Python, Linux and AWS to gain different perspectives of the computing world.
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Section Introduction Transcripts
Course Overview
Data keeps growing, and the demand for professionals who can process data also keeps growing. As more and more organizations use AWS to process their data, how can you keep up with the fast evolving technologies on AWS? Hi, I'm Dan. I'm a senior software engineer with a PhD in Software Architecture and two decades of software engineering experience in various roles. I enjoy helping people grow their skills. So with help from the awesome Pluralsight team, I prepare this course for you to get the fundamentals of data processing with AWS and help you earn the AWS Data Analytics certification. Here is the plan. First, let's look at how to process data using the Lambda and Glue Amazon services. Second, let's understand the big picture about the Hadoop ecosystem, which is so influential in data processing. Third, we process data with the Elastic MapReduce service. Finally, let's automate data processing using the Data Pipeline service. As prerequisites, you need some basic knowledge of services such as S3 and EC2. To reproduce the demos in this course, you need access to the AWS Management Console and sufficient rights.