This investigation presents a comprehensive analysis of the historical trajectory of sunspot number (SSN) observations in Egypt, a country renowned for its rich astronomical heritage. Despite Egypt's long-standing practice in solar observation, the local SSN datasets are marred by a significant incidence of missing entries, posing formidable obstacles to the accurate evaluation of solar activity. Addressing this challenge, the study employs dynamic time warping (DTW) as a methodological tool to assess the alignment of local and global SSN datasets. This technique adeptly harmonizes these datasets by reconciling temporal inconsistencies and variations in sampling rates. Subsequent to the application of DTW, the research integrates orthogonal regression for the imputation of the absent values in the Egyptian SSN dataset. This method, preferred for its proficiency in managing errors in both the dependent and independent variables, deviates from conventional linear regression techniques, thereby providing a more nuanced approach to data approximation. The analysis unveils a substantial correlation between the estimated local SSN values and the global SSN indices, with the former consistently exhibiting lower figures. Nevertheless, these local values display parallel trends and seasonal fluctuations akin to those observed in the global dataset, validating the imputation method and highlighting the unique characteristics of the Egyptian SSN data within the global context of solar activity monitoring. The implications of these findings are significant for the discipline of solar physics, especially for regions contending with incomplete datasets. The methodologies advanced in this research offer a robust framework for the enhancement of datasets with missing data, thus broadening the comprehension of solar phenomena.