In the dynamic landscape of contemporary corporate operations, extracting knowledge from business processes has emerged as a pivotal factor influencing the success and sustainability of companies. This paper delves into the growing significance of using knowledge extracted from business processes to achieve organizational goals and objectives, shedding light on how it has become central to a company’s overall functioning. As businesses increasingly rely on streamlined processes to gain a competitive edge, the impact of insufficient data quantity on these processes must be balanced. Many companies need help with the challenges posed by inadequate data, impeding their ability to make informed decisions and hindering operational efficiency. This research explores the intricate relationship between process mining and data quantity, unraveling the repercussions of suboptimal data practices on organizational performance in business intelligence. It aims to provide a novel approach involving data augmentation to mitigate this problem, allowing companies that rely on poorly logged processes to benefit from process mining and business process alignment.