The study objectives were to shed light on adopting big data analytics technologies in leading mobile telecommunications companies in Egypt, focusing on the moderating role of resistance to technological change.), they were applied to a pilot sample of 80 respondents. Following the observation of the results, they were processed. The Pearson correlation coefficient was calculated between the factors and the total scale score, Reliability coefficients for the scales (Adopting big data analytics, Moderating Role of Resistance to Technological Change) were calculated using Cronbach's Alpha coefficient after that, the researcher used an analytical descriptive strategy to test their hypotheses. The study's instrument, a questionnaire, was disseminated after being assessed and arbitrated by multiple experts on a sample. Participants in the study were random customers of mobile Telecommunication companies Vodafone, Orange, Etisalat, and We) in Egypt the sample was (385) and (350) were retrieved with a percentage of Recovery equal to (91%), according to the study's findings. Uncovering these underlying drivers shows significant differences between males and females in their perceptions or implementations of Big Data Analytics. Males reported a higher mean score (67.17) than females (63.9). This difference is statistically significant (p < 0.001), suggesting that gender does play a role in how Big Data Analytics is perceived or implemented within the organization. The study provides valuable insights into strategies for fostering a culture of innovation and overcoming barriers to technology adoption within the telecommunications industry. It also significantly contributes to the theoretical understanding of technology acceptance and change management processes in the context of the telecommunications sector. Ultimately, this research provides actionable recommendations for mobile telecommunications companies in Egypt, guiding them on effective strategies to leverage the power of big data analytics while navigating the complexities of organizational change. By addressing resistance to technological change and promoting a culture of data-driven decision-making, these companies can enhance customer experiences, optimize operations, and maintain a competitive edge in an increasingly data-driven landscape.