<![CDATA[In knowledge-intensive firms, the ability to make informed and timely strategic decisions is increasingly reliant on data-driven insights. Data mining maturity, defined as the level of sophistication in an organization's data mining capabilities, plays a critical role in shaping decision-making processes. Predictive analytics, which utilizes data to forecast future trends, has been proposed as a key mediator in this relationship, enhancing the ability of firms to make accurate and efficient decisions. This study explores the interplay between data mining maturity and strategic decision-making, specifically assessing the mediating role of predictive analytics. The research uses a mixed-methods approach, combining quantitative surveys and structural equation modeling (SEM) to examine data from 200 knowledge-intensive firms. The results reveal a significant positive relationship between data mining maturity and decision-making outcomes, with predictive analytics mediating this relationship and accounting for 45% of the variance in decision quality and 38% in decision speed. The study concludes that firms with higher data mining maturity, coupled with effective use of predictive analytics, make faster and more accurate strategic decisions. These findings provide empirical evidence that integrating predictive analytics into decision-making processes significantly enhances the effectiveness of data mining systems.]]>
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