  In this note, we explore a middle ground between data-driven model reduction
and data-driven control. In particular, we use snapshots collected from the
system to build reduced models that can be expressed in terms of data. We
illustrate how the derived family of reduced models can be used for data-driven
control of the original system under suitable conditions. Finding a control law
that stabilizes certain solutions of the original system as well as the one
that reaches any desired state in final time are studied in detail.
