  In the era of precision cosmology, ensuring the integrity of data analysis
through blinding techniques is paramount -- a challenge particularly relevant
for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a
monumental effort to map the cosmic web, with the goal to measure the redshifts
of tens of millions of galaxies and quasars. Given the data volume and the
impact of the findings, the potential for confirmation bias poses a significant
challenge. To address this, we implement and validate a comprehensive blind
analysis strategy for DESI Data Release 1 (DR1), tailored to the specific
observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO),
Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We
carry out the blinding at the catalog level, implementing shifts in the
redshifts of the observed galaxies to blind for BAO and RSD signals and weights
to blind for PNG through a scale-dependent bias. We validate the blinding
technique on mocks, as well as on data by applying a second blinding layer to
perform a battery of sanity checks. We find that the blinding strategy alters
the data vector in a controlled way such that the BAO and RSD analysis choices
do not need any modification before and after unblinding. The successful
validation of the blinding strategy paves the way for the unblinded DESI DR1
analysis, alongside future blind analyses with DESI and other surveys.
