This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the specialization.
In this specialization, you will gain hands-on experience with AWS services used for big data collection, storage, processing, and analysis. Explore Amazon S3, DynamoDB, Kinesis, and other AWS tools to manage large-scale data. Learn about real-time data streaming and processing techniques, integrating services like Lambda and Glue, all while focusing on security practices for big data in the AWS cloud.
The journey starts with data collection through Kinesis, IoT, and SQS, followed by storage techniques using S3 and DynamoDB. You will then explore data processing with Lambda and Glue, automating workflows. Finally, you’ll dive into data analytics using Athena, Redshift, and Elasticsearch, while learning to visualize data with QuickSight and manage security with IAM and CloudTrail.
This specialization is ideal for professionals with basic AWS knowledge, aiming to specialize in big data. It's designed for cloud architects, data engineers, and developers with prior AWS experience. While prior knowledge is recommended, all key concepts are thoroughly covered.
By the end of the specialization, you will be able to design data workflows, use AWS services to process big data, and ensure security across your data management tasks.
Applied Learning Project
Throughout this specialization, you will work on real-world projects that involve building and managing data pipelines, performing data analysis using Athena and Redshift, and creating secure environments for big data workflows. These hands-on projects will enable you to apply your skills to authentic business scenarios, solidifying your understanding of AWS services in a practical context.
