This course covers all aspects of hosting big data on the Amazon Web Services (AWS) platform, and will prepare you to confidently perform distributed processing.
The course begins with an overview of exam details and the recommended AWS knowledge you need before starting the course. It then takes you through topics relating to big data on AWS such as cloud computing and deployment, databases and data warehousing in AWS, and AWS services for big data. Next, you’ll move on to learn about data collection within big data on AWS which will cover data producers and consumers, IoT and big data, and Kinesis Firehose. As you advance, you’ll get to grips with the storage and processing aspects of big data on AWS, covering DynamoDB, AWS aurora in big data, and Amazon EMR. Finally, you’ll delve into visualization and security, and create a project for analyzing large datasets.
By the end of this course, you will have learned about cloud-based big data solutions, and be able to use AWS Elastic MapReduce to process data and create big data environments.
The resources for this course is available at https://github.com/PacktPublishing/AWS-Certified-Big-Data-Specialty-Cer…
Discover the design principles of AWS cloud architecture
Understand why AWS is used for big data along with the challenges involved in using it
Get to grips with DynamoDB, machine learning, and Lambda
Find out how to transfer data using Lambda
Delve into DynamoDB stream and cross-region replication
Explore DynamoDB performance and partition key selection