The Data as a Service (DaaS) pattern allows for the delivery of the Minimal Viable Product (MVP) for real-time data management, while avoiding many of the anti-patterns that traditional data provisioning and BI systems portray. Unlike traditional BI tooling, building out a DaaS system doesn't require high up-front costs and the welding of multiple products.
The DaaS Pattern is the cobination of three logical components Data Model, Processing, and Eventing.
The data model mimics an envelope, (DaaS Document) with metadata as the wrapper and the data object as the content. Because of this data model, the orchestration of the eventing can be driven by the data and does not have to be preconfigured.
The processing can be supported by microservices or serverless functions, while the role of eventing is fulfilled by a broker. Since brokering supports the publish/subscribe pattern, a plugin model of data provisioning steps can be easily added/removed and it even allows for forked parallel processing on a singluar data message.
