This paper provides an overview of atmospheric data assimilation. It is shown bow data assimilation developed historically from the requirement to provide initial conditions for numerical weather prediction. The basic concepts of atmospheric data assimilation are discussed, starting with the scalar case, and progressing through three dimensional spatial analysis to the full four dimensional problem. The most advanced algorithms (4DVAR and the Kalman filter) are introduced briefly and their relation to the simpler algorithms explored. The control of undesirable high frequency oscillations is sketched. The present state of atmospheric data assimilation is discussed and possible future developments are suggested.