Big data analysis in strategic management significantly aids decision-making processes, enhancing their effectiveness. Investigating key themes in this area allows for trend identification, process optimization, and proactive issue prediction, thereby boosting competitiveness. This study aims to develop a visual tool for decision-making support regarding sales behaviour in the operations department of a service industry, utilizing big data analysis within Industry 4.0. The research methodology used was the Design Science, identifying 5 main phases to accomplish the objective. It was applied the IDC model to centralizes the management of data and establish decision-making requirements. Subsequently, the DMN method for describing and modeling repeatable decisions within organizations and data architecture were applied, facilitating the comprehension of the significance and scope of the studied topic, along with its main themes. Utilizing Power Query, data analysis and processing were automated, and M language codes were programmed. It was concluded that data quality’s relevance significantly impacts decision-making within strategic management, thus enabling the development of digital transformation within the organization.