Abstract: A computer-implemented system and method for dynamically generating library reports is provided. An application server may acquire and receive a plurality of raw item datasets each associated with a library item from multiple sources; and map each of the plurality of raw item datasets to a set of parameters to generate a mapped item dataset for each library item by identifying a unique identifier for each raw item dataset associated with each library item. and process a plurality of mapped item datasets to output processed item datasets that corresponds to one or more metrics. The application server may dynamically generate one or more library reports by applying a machine learning algorithm on the processed item datasets. The machine learning algorithm is executed to determine a priority of generating each library report based at least on a user request.

Abstract: A computer-implemented system and method for dynamically generating library reports is provided. An application server may acquire and receive a plurality of raw item datasets each associated with a library item from multiple sources; and map each of the plurality of raw item datasets to a set of parameters to generate a mapped item dataset for each library item by identifying a unique identifier for each raw item dataset associated with each library item. and process a plurality of mapped item datasets to output processed item datasets that corresponds to one or more metrics. The application server may dynamically generate one or more library reports by applying a machine learning algorithm on the processed item datasets. The machine learning algorithm is executed to determine a priority of generating each library report based at least on a user request.