Rewrite: Descriptive Analytics Summary Within the analytics framework, dimensional metrics such as the download rate, registered users, and active users provide constructive and valuable insights into the effectiveness of the LEAP application. The analysis of Mi-Org's LEAP application involves three main types of analytics: descriptive, predictive, and prescriptive. Descriptive analytics addresses concerns aimed at knowing "What has happened?" by examining data such as the number of users and recurring monthly sales. Predictive analytics, on the other hand, evaluates the application's potential future performance and answers the question, "What is likely to happen next?" Following this, prescriptive analytics provides recommendations for action by assessing the likelihood of different future scenarios and responding to the question, "What is the best course of action for Mi-Org?" (UMGC, 2025). Given the substantial volume of data, examining additional data related to veterans is critical for a comprehensive evaluation of the LEAP application. The application's classification tree algorithm has identified that the most significant predictor of whether a soldier secures employment after transitioning from military service is the presence of a PTSD diagnosis, as illustrated in Figure 1 (UMGC, 2025). On the other hand, the LEAP App only addresses fundamental descriptive statistics such as mean, mode, and median (Lizard, 2022). It uses straightforward descriptive analysis for a si