The future of data will be self-service, with users opening consoles to define the pieces they need, format them, and spin up new endpoints such as databases, caches, microservices, or serverless functions. Event-driven architectures are becoming increasingly popular, allowing companies to store, join, aggregate, and reform data from across a company before pushing it wherever needed. There are four broad patterns of event-driven architectures: global event streaming platforms, central event stores, event-first applications, and automated data provisioning. Companies often adopt one pattern at a time, with many implementing some version of these futures already in production. Streaming platforms can cache events for defined periods or store them indefinitely, creating organizational ledgers or event stores. Event storage is required for stateful stream processing, enriching orders with customer or account information, and providing denormalized input for databases. Traditional applications often work by importing datasets into their database, but event-driven architectures push real-time events directly into microservices or serverless functions, simplifying the development process while making systems more responsive and efficient.