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Developed for Veritas Technologies LLC, this project optimizes DB workloads by predicting future file accesses and caching them in advance. Utilizing inotify for file event monitoring and Python for training a Random Forest model, it enhances efficiency and reduces latency compared to traditional caching methods, adapting to dynamic data access.