Explore how to implement containers and data management on popular cloud platforms like Amazon Web Services (AWS) and Google Cloud Platform (GCP) for data science. Planning big data solutions, disaster recovery, and backup and restore in the cloud are also covered in this course. Key concepts covered here include cloud migration models from the perspective of architectural preferences; prominent big data solutions that can be implemented in the cloud; and the impact of implementing Kubernetes and Docker in the cloud, and how to implement Kubernetes on AWS. Next, learn how to implement data management on AWS, GCP, and DBaaS; how to implement big data solutions using AWS; how to build backup and restore mechanisms in the cloud; and how to implement disaster recovery planning for cloud applications. Learners will see prominent cloud adoption frameworks and their associated capabilities, and hear benefits of and how to implement blockchain technologies or solutions in the cloud. Finally, learn how to implement Kubernetes on AWS, build backup and restore mechanisms on GCP, and implement big data solutions in the cloud.
Cloud Data Architecture: Data Management & Adoption Frameworks