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This study examines the impact of Big Data technologies on operational efficiency in DP World’s supply chain and logistics operations. Employing a mixed-methods approach, we surveyed 405 stakeholders and performed 20 semi-structured interviews to investigate the incorporation of advanced analytics, machine learning, and real-time processing capabilities. The study employs Technology-Organization-Environment (TOE) and economic frameworks to examine the technological, organisational, environmental, and economic determinants affecting Big Data adoption. Results indicate substantial positive effects on the reduction of operational complexity, enhancement of customer responsiveness, improvement of supplier connections, and strengthening of technical partnerships. PLS-SEM analysis utilising ADANCO software validated all hypotheses, demonstrating robust connections between Big Data deployment and supply chain efficiency measures. Essential findings indicate that governmental assistance, organisational culture, and information technology infrastructure are crucial success determinants. The report offers practical advice for supply chain managers and policymakers, emphasising Big Data's revolutionary capacity for competitive advantage in global logistics operations.

<div><p>Data mining technology is one of the new technologies that have become increasingly popular. Data mining enables to form forecasts and models regarding future by making use of past data. It can be costly, risky and time consuming for enterprises to gain knowledge. Firms gain important competitive advantage by data mining methods. This study analyzes on the readiness to implement and the extent of utilization of data mining technologies in the Financial Information Systems (FIS) in Borsa Istanbul and also researches the level of understanding of, perceptions of and readiness to implement data mining technologies within the Borsa Istanbul.  Analysis was undertaken using SPSS. Manufacturing and financial enterprises are the universal of this study. Primary data were obtained by using survey method and questionnaire technique and findings of the study were evaulated. Technological, organisational and human resources issues had a significant role in the decision to, or not to utilize data mining technology. The ability to use data mining technology was found to be increased the performance of the Financial Information System.<strong></strong></p></div>