Realizing that data-driven decisions have grown rapidly over the past few years as an essential segment of business intelligence, researchers have keenly found interest in explore this area further. Data-driven decisions and digital asset management have been approached by insightful researchers within a well-integrated theoretical framework taking into account psychological, managerial and operational dimensions, evaluating the effect of these dimensions on decisions and deliberately dissecting the process of collecting, storing, processing, analyzing and managing digital assets. using data. Data-driven decisions have significantly improved the quality of decisions by strengthening decision-making mechanisms and increasing their efficiency, replacing the intuition-based approach that suffers from exacerbations of structural and operational problems. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay Empirical examination of data-driven decisions and quantitative assessment of the impact of such a tool has become essential. Recent evidence from business and information technology management literature and non-academic business-focused articles has shown increasing interest in approaching digital asset management in a quantifiable approach. Specifically, the scrutiny of data-driven decisions and new digital asset management tools is actually a manifestation of collecting, manipulating, storing, and processing data competently. Additionally, the variable “not having data-trained staff” is consistent with what has been written and discussed in the literature as a potential cause of several compounding difficulties in the market economy; this is largely due to the lack of data-driven tools by decision-makers and employees (Streifer and Goens, 2004). Effective use of data and the latest digital asset management technologies requires the use of these tools by businesses and businesses planning to expand in the contemporary world. walk. This is consistent with what Leibowitz (2013) argues regarding the transformative role of statistical records with respect to the decision-making process. This chapter attempts to discuss the empirical findings of the article, citing and integrating findings from the literature, ensuring that our conclusions are based on sound theoretical and empirical foundations. Quantitative data has been introduced at every essential step of the decision-making processes, proving the effectiveness and reliability of these methods. The literature is replete with such studies, such as that of Liebowitz (2013), who argues that matching historical records with our current status quo gives humans psychological comfort in all types of decision-making situations. In fact, well-constructed models are analogous to how our brains work. Therefore, using data-driven decision-making approaches is like emulating how our human brain works. Thus, this section aims to empirically unveil the effect of data-driven decisions and the impact of digital asset management on business performance by meticulously extracting our regression results. statistical models and tests, organizing concepts and ideas from the literature that relate to our meaningful variables and drawing relevant policy implications. It should be noted that this empirical approach.