Cloud. Data.

Warehousing. The mythos conjured by three simple words has taken marketing to new levels of hyperbole.

Cloud data warehousing, together with AI (of course) will change all business decision making and action taking. In addition to the expected cloud data warehouse model, three new delivery patterns have been spawned: data lakehouse, fabric, and mesh.

However, as seen in Volume I of this series, the conceptual and logical architectures change only minimally as we move from on premises to the cloud. So, why these very different solutions? In Volume II, Dr.

Barry Devlin—a founder of data warehousing—offers a framework of architectural design patterns (ADPs) to allow implementers to easily compare and contrast these different, proposed solutions. To evaluate their pros and cons according to a common model and in consistent terms.

To choose an approach best suited to particular business needs and specific technical starting points. And looking to the behemoth of AI bearing down upon us, Barry proposes a set of conceptual models that allow possible answers to the foundational questions: In a world of burgeoning data and information, how do we really make decisions and should we entrust them to AI built upon cloud data warehousing?.