  The SKA will be capable of producing a stream of science data products that
are Exa-scale in terms of their storage and processing requirements. This
Google-scale enterprise is attracting considerable international interest and
excitement from within the industrial and academic communities. In this chapter
we examine the data flow, storage and processing requirements of a number of
key SKA survey science projects to be executed on the baseline SKA1
configuration. Based on a set of conservative assumptions about trends for HPC
and storage costs, and the data flow process within the SKA Observatory, it is
apparent that survey projects of the scale proposed will potentially drive
construction and operations costs beyond the current anticipated SKA1 budget.
This implies a sharing of the resources and costs to deliver SKA science
between the community and what is contained within the SKA Observatory. A
similar situation was apparent to the designers of the LHC more than 10 years
ago. We propose that it is time for the SKA project and community to consider
the effort and process needed to design and implement a distributed SKA science
data system that leans on the lessons of other projects and looks to recent
developments in Cloud technologies to ensure an affordable, effective and
global achievement of SKA science goals.
