This article gives a brief account on digital control, particularly sampled-data control where signals are sampled with a uniform rate. We first review basic notions such as sampling and hold, digital-to-analog (DA) converter, z-transform, and pulse transfer functions. The relationship of sampling theorem with aliasing and controllability is also reviewed. We then discuss standard classical design methodologies and problems inherent to them. The problem lies in the fact that sampled-data systems operate on two time sets - continuous and discrete. This is usually the cause of difficulties encountered in the classical design methods, in particular the oscillatory intersample behavior called ripples. This problem is resolved by introducing a new technique called lifting. It is seen that lifting makes linear continuous-time time-invariant plant an infinite-dimensional discrete-time system, thereby making the total system a time-invariant discrete-time system. Time-invariant notions, such as steady-state response, frequency response, transfer functions, can then be fully recovered. This framework makes it possible to formulate and solve robust control such as H2 and H-infinity control and improve upon the continuous-time performance dramatically. The same design philosophy is then applied to digital signal processing, where one can use this robust control method to optimize the intersample signals optimally. Robust sampled-data control is suitably applied to the signal processing context, and is seen to optimally reproduce intersample high-frequency signals. Applications to digital signal processing are discussed. The article concludes with reviews on the existing literature and recent advances in sampled-data control as well as discussing some future directions.