Video: .MP4, AVC, 1920x1080, 30 fps | Audio: English, AAC, 44.1 KHz, 2 Ch | Duration: 55m | 794 MB

Instructor: Stuart Scott

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 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 its 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