Summary
In this chapter, we concluded the book by providing you with options for automating your data platform. We looked at DevOps, DataOps, and MLOps as the three ways to completely automate and operationalize your data platform.
In the DevOps process, we looked at how CI/CD and Iac help organizations with an automated, repeatable, and organized way to operationalize their AWS infrastructure, services, and the features inside those services. DataOps focuses on simplifying the data pipelines by leveraging orchestration services such as Amazon MWAA and AWS Step functions. MLOps on the other hand helps to manage the entire life cycle of the ML process and Amazon SageMaker provides capabilities to make MLOps a seamless process.
Finally, we looked at how organizations can monetize their data by either using DaaS, insights-as-a-service, or API-as-a-service. All organizations have the common goal of deriving value from their data platform, either directly by monetizing the data or...
