The invention of data warehouse automation (DWA) as a technology category
was inevitable. And it was invented in a real sense: the first DWA tools evolved
to address gaps in the development, deployment, and maintenance of data
A data warehouse is always bespoke to a degree, custom-tailored to the size,
activities, and priorities of the business. Although it does not necessarily follow
that the technologies, processes, and practices underpinning and supporting the
data warehouse must also be of bespoke design, IT practitioners nevertheless
continue to design the equivalent of bespoke data warehouse systems. The
practical effect is that each new data warehouse is a greenfield project, at least
as regards the configuration, orchestration, and maintenance of the technologies
— and to a lesser degree, of the processes and practices — that comprise it. This
is the chasm that DWA as a technology category evolved to bridge.
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