The analysis of low-multipoles from SKA continuum surveys can benefit from the methods developed for the study of the CMB. Missing sky area is always a problem for low-mode measurements. For CMB studies, many methods were proposed to deal with a mask of missing **data** for both power spectrum estimation and phase recovery. For the power spectrum, one of the most used methods is MASTER (Hivon et al. 2002). It consists in first building a matrix which captures the coupling between the modes induced by the mask, and then inverting this matrix. In Figure 4 we plot the angular power spectrum of SKA galaxies for low-mulitpoles with error bars corresponding to a SKA1 continuum survey. For phase recovery, or more generally for large scale map reconstruction, many methods have been proposed based on Wiener filtering, l 2 or l 1 norm regularization, constraint realizations or diffusion [see Starck et al. (2013) and references therein]. Based on these new methodological idea, Planck **data** were analyzed with a mask removing 27% of the sky (Planck collaboration 2014c; Rassat et al. 2014). For a given observed sky area, the shape of the mask will also be important. The importance of random sampling is also described in Paykari et al. (2013), and many small missing parts, randomly distributed, will always be much better for large scale studies than a compact big missing part.