In this 'Back to Basics' episode, Franklin discusses maintaining data consistency in microservice architectures using the Saga pattern with AWS Step Functions. He explains how distributed transactions across multiple services can lead to partial failures and data inconsistencies. The Saga pattern is presented as a solution, using compensating transactions to undo changes in case of failures. Franklin demonstrates this concept with an example of a flight and car rental booking system, showing how Step Functions can orchestrate the process and handle failures gracefully. This approach ensures data consistency while keeping microservices loosely coupled and independent.