Data integration demand management using artificial intelligence

A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

• to obtain at least one data integration demand, wherein the at least one data integration demand comprises textual information provided by at least one user;
• to determine multiple parameters of the at least one data integration demand by applying one or more machine learning natural language processing techniques to at least a portion of the textual information provided by the at least one user;
• to generate at least one delivery date prediction for the at least one data integration demand by applying one or more artificial intelligence techniques to the multiple determined parameters of the at least one data integration demand, wherein applying the one or more artificial intelligence techniques comprises processing at least a portion of the multiple determined parameters using at least one artificial neural network, and wherein one or more neurons of at least one input layer of the at least one artificial neural network correspond to one or more delay sources associated with the at least one generated delivery date prediction;
• and
• to perform one or more automated actions based at least in part on the at least one generated delivery date prediction, wherein performing the one or more automated actions comprises automatically modifying one or more resource allocations, within at least one enterprise associated with resolving the at least one data integration demand, in accordance with the at least one generated delivery date prediction.

An apparatus comprising:

• at least one processing device comprising a processor coupled to a memory;
• the at least one processing device being configured:
• to obtain at least one data integration demand, wherein the at least one data integration demand comprises textual information provided by at least one user;
• to determine multiple parameters of the at least one data integration demand by applying one or more machine learning natural language processing techniques to at least a portion of the textual information provided by the at least one user;
• to generate at least one delivery date prediction for the at least one data integration demand by applying one or more artificial intelligence techniques to the multiple determined parameters of the at least one data integration demand, wherein applying the one or more artificial intelligence techniques comprises processing at least a portion of the multiple determined parameters using at least one artificial neural network, and wherein one or more neurons of at least one input layer of the at least one artificial neural network correspond to one or more delay sources associated with the at least one generated delivery date prediction;
• and
• to perform one or more automated actions based at least in part on the at least one generated delivery date prediction, wherein performing the one or more automated actions comprises automatically modifying one or more resource allocations, within at least one enterprise associated with resolving the at least one data integration demand, in accordance with the at least one generated delivery date prediction.