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Process Data Publishing is a database design approach that focuses on isolating the underlying data storage and presentation layers from each other. This strategy aims to reduce the complexity in the database by distributing the data management and retrieval across separate processes.

The Data Access Object (DAO) pattern is commonly used in conjunction with this approach. In this setup, an independent DAO serves as a bridge between the business layer and the storage layer, ensuring secure and efficient data access.

Key features of process data publishing include data decoupling, eliminate external dependence on data format or location, and dividing the data management concerns across different processes. This separation enables more efficient and scalable database management, and coping with changes and updates.

In the process data publishing architecture, the business layer receives preprocessed data, thus simplifying the retrieval and processing of data. Access to the consolidated data objects is thus decoupled from the underlying data storage.

Web services, custom-reporting APIs, ad-hoc data processors, and reports are samples of the kinds of interfaces that can talk to the core data organization and unleash further functionality to clients via process data publishing. It ramps up the expressive power and does it down to the lower-information platform based that reduces chatter and delivers data down-line.