The Gaussian scale-space is widely being used in human vision problem. It can be used to smooth the data by filtering off low frequency of the signal. In this paper we will discuss the applications of Gaussian scale-space in data smoothing problem arising in financial (Kuala Lumpur Composite Index (KLCI)) and electroencephalogram (EEG) problem. We also show the comparison between Gaussian scale-space and Discrete Wavelet Transform (DWT) for data smoothing. Overall results indicated that Gaussian scale-space gave a good result. © 2011 IEEE.