Introduction3m 7s
Data Encryption
Overview of Encryption6m 23s
AWS Service Encryption
Amazon S3 and Amazon Athena Encryption12m 5s
Elastic MapReduce (EMR) Encryption6m 12s
Relational Database Service (RDS) Encryption4m 53s
Amazon Kinesis Encryption5m 28s
Amazon Redshift6m 37s
Summary10m 11s

Start course

Duration54m 56s


Resources mentioned throughout this course:

Cloud Academy Courses:

AWS Resources:

Course Description

The use of Big Data is becoming commonplace within many organizations that are using Big Data solutions to perform large scale queried data analysis with business intelligence toolsets to gain a deeper understanding of data gathered.

Within AWS, this data can be stored, distributed and consumed by various different services, many of which can provide features ideal for Big Data analysis. Typically, these huge data sets often include sensitive information, such as a customer details or financial information.

With this in mind, security surrounding this data is of utmost importance, and where sensitive information exists, encryption should be applied against the data.

This course firstly provides an explanation of data encryption, and the differences between symmetric and asymmetric cryptography. This provides a good introduction before understanding how AWS implements different encryption mechanisms for many of the services that can be used for Big Data. These services include:

  • Amazon S3
  • Amazon Athena
  • Amazon Elastic MapReduce (EMR)
  • Amazon Relational Database Service (RDS)
  • Amazon Kinesis Firehose
  • Amazon Kinesis Streams
  • Amazon Redshift

The course covers encryptions options for data when it is at both at-rest and in-transit and contains for the following lectures:

  • Introduction: This lecture introduces the course objectives, topics covered and the instructor
  • Overview of Encryption: This lecture explains data encryption and when and why you may need to implement data encryption
  • Amazon S3 and Amazon Athena Encryption: This lecture dives into the different encryption mechanisms of S3, from both a server-side and client-side perspective. It also looks at how Amazon Athena can analyze data sets stored on S3 with encryption
  • Elastic MapReduce (EMR) Encryption: This lecture focuses on the different methods of encryption when utilizing EMR in conjunction such as EBS and S3. It also looks at application specific options with Hadoop, Presto, Tez and Spark
  • Relational Database Service (RDS) Encryption: This lecture looks at the encryption within RDS, focusing on it’s built in encryption plus Oracle and SQL Server Transparent Data Encryption (TDE) encryption
  • Amazon Kinesis Encryption: This lecture looks at both Kinesis Firehose and Kinesis Streams and analyses the encryption of both services.
  • Amazon Redshift Encryption: This lecture explains the 4 tiered encryption structure when working with Redshift and KMS. It also explains how to encrypt when working with CloudHSM with Redshift.
  • Summary: This lecture highlights the key points from the previous lectures

About the Author

Learning paths11

Stuart has been working within the IT industry for two decades covering a huge range of topic areas and technologies, from data centre and network infrastructure design, to more recently cloud architecture and implementation.

He is a Certified Data Centre Design Professional (CDCDP), with his latest achievements gained within the Amazon Web Services (AWS) field.

He currently holds the AWS Certified Solutions Architect - Associate certification as well as accreditations as an AWS Business and Technology Professional and in TCO and Cloud Economics.

In January 2016 Stuart was awarded 'Expert of the Year Award 2015' from Experts Exchange for his knowledge share within cloud services to the community.

Stuart enjoys writing about cloud technologies and you will find many of his articles within our blog pages.