  The PandaX-4T experiment is designed for multiple purposes, including
searches for solar neutrinos, weakly interacting massive particles, and rare
double beta decays of xenon isotopes. The experiment produces a huge amount of
raw data that needs to be stored for related physical analyses in a wide energy
range. With the upgrading of the PandaX-4T experiment, the doubled sampling
rate resulted in a larger data size, which challenges both the cost and the
data processing speed. To address this issue, we propose a data reduction
strategy by removing the noise tail of large signals and downsampling the
remaining parts of them. This strategy reduces the requirement for storage by
65% while increasing data processing speed. The influences on physical analyses
on different topics at different energy regions are negligible.
