This study aims to comprehensively delineate the mechanization of empirical data collection and processing techniques through a rigorous case illustration, specifically focusing on the development of a digital textbook in the form of a chemistry e-book integrated with the STEAM (Science, Technology, Engineering, Arts, and Mathematics) approach. Within the research and development (R&D) framework, methodological precision in extracting raw data into valid information frequently poses a crucial obstacle for novice researchers, particularly regarding interpretation bias. Utilizing a descriptive quantitative approach combined with simulation modeling, this article demonstrates the operational flow of product feasibility data sequentially through five interconnected technical stages: editing, coding, tabulating, analyzing, and visualizing. The operationalized data collection instruments encompass expert validation sheets (content and media specialists) alongside a 5-point Likert scale user readability response questionnaire. The simulation analysis results on test data indicate that the calculation of central tendency parameters (mean, median, and mode) alongside standard deviation precision metrics can objectively and transparently map the e-book's practicality and validity levels. The simulated data computation reveals that the average feasibility score for the STEAM aspect falls into the highly valid category, strongly supported by a low standard deviation value indicating a high consensus of expert perceptions. Through the deconstruction of this case illustration, descriptive statistics are proven to function not merely as mechanical calculation tools on paper, but as vital preliminary diagnostic instruments ensuring the academic accountability of developed teaching materials before their broad implementation in school-level chemistry education. Keywords: Data Processing, Research and Development, Chemistry E-Book, STEAM Approach, Descriptive Statistics