# US 2021/0241087 A1 · Data Integration Demand Management Using Artificial Intelligence > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0241087 A1 - Document ID: US20210241087A1 - Status: Published application - Kind: A1 - Application number: 16/776,900 - Filed: 2020-01-30 - Published: 2021-08-05 - Earliest claimed: 2020-01-30 - Assignees: Dell Products L.P. - Applicants: Dell Products L.P. - Inventors: Hung T. Dinh; Sandeep Govindraj; Ranjani Muthyam Venkata; Sabu K. Syed; Kannappan Ramu - Web page: https://patentgrep.com/patent/US20210241087A1 ## CPC - G06N 3/08: Learning methods - G06F 40/216: using statistical methods - G06F 40/30: Semantic analysis - G06N 3/04: Architecture, e.g. interconnection topology - G06N 3/0499: Feedforward networks - G06N 3/086: using evolutionary algorithms, e.g. genetic algorithms or genetic programming - G06N 3/09: Supervised learning - G06N 3/0985: Hyperparameter optimisation; Meta-learning; Learning-to-learn - G06N 3/10: Interfaces, programming languages or software development kits, e.g. for simulating neural networks - G06N 20/00: Machine learning - G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Methods, apparatus, and processor-readable storage media for data integration demand management using artificial intelligence are provided herein. An example computer-implemented method includes obtaining at least one data integration demand, wherein the at least one data integration demand comprises textual information provided by at least one user; determining 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; generating 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; and performing one or more automated actions based at least in part on the at least one generated delivery date prediction. ## Claims ### Claim 1 A computer-implemented method comprising: obtaining at least one data integration demand, wherein the at least one data integration demand comprises textual information provided by at least one user; determining 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; generating 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; and performing one or more automated actions based at least in part on the at least one generated delivery date prediction; wherein the method is performed by at least one processing device comprising a processor coupled to a memory. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein applying the one or more artificial intelligence techniques comprises passing the multiple determined parameters through at least one neural network. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein applying the one or more artificial intelligence techniques comprises passing the multiple determined parameters through at least one artificial neural network multilayer perceptron. ### Claim 4 (depends on 3) The computer-implemented method of claim 3, wherein one or more neurons of at least one sub-layer of an input layer of the at least one artificial neural network multilayer perceptron symbolize one or more delay sources associated with the at least one generated delivery date prediction. ### Claim 5 (depends on 4) The computer-implemented method of claim 4, wherein activation of one of the one or more neurons represents plausibility of a respective one of the one or more delay sources being a source of delay, of an amount above a given threshold level, associated with the at least one generated delivery date prediction. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein performing the one or more automated actions comprises computing a confidence value attributed to the at least one generated delivery data prediction based at least in part on a level of complexity associated with the at least one data integration demand. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, 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. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein performing the one or more automated actions comprises outputting, to at least one integration repository, the at least one generated delivery date prediction and the multiple determined parameters of the at least one data integration demand. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein performing the one or more automated actions comprises training the one or more artificial intelligence techniques using the at least one generated delivery date prediction and the multiple determined parameters of the at least one data integration demand. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein performing the one or more automated actions comprises outputting, to the at least one user, the at least one generated delivery date prediction. ### Claim 11 (depends on 10) The computer-implemented method of claim 10, further comprising: modifying at least one of the multiple determined parameters of the at least one data integration demand in response to input from the at least one user obtained in connection with the at least one generated delivery date prediction. ### Claim 12 (depends on 1) The computer-implemented method of claim 1, wherein the multiple parameters comprise information pertaining to two or more of: digital segment, initial delivery date, application status, type of engagement, type of data, external integration, average volume, maximum volume, average payload size, maximum payload size, parallelism, message service level agreements, message orchestration, message enrichment, one or more necessary security levels, one or more integration products, at least one data sender, at least one data receiver, product stability, and integration complexity. ### Claim 13 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; and to perform one or more automated actions based at least in part on the at least one generated delivery date prediction. ### Claim 14 (depends on 13) The non-transitory processor-readable storage medium of claim 13, wherein applying the one or more artificial intelligence techniques comprises passing the multiple determined parameters through at least one neural network. ### Claim 15 (depends on 13) The non-transitory processor-readable storage medium of claim 13, wherein applying the one or more artificial intelligence techniques comprises passing the multiple determined parameters through at least one artificial neural network multilayer perceptron. ### Claim 16 (depends on 13) The non-transitory processor-readable storage medium of claim 13, wherein performing the one or more automated actions comprises computing a confidence value attributed to the at least one generated delivery data prediction based at least in part on a level of complexity associated with the at least one data integration demand. ### Claim 17 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; and to perform one or more automated actions based at least in part on the at least one generated delivery date prediction. ### Claim 18 (depends on 17) The apparatus of claim 17, wherein applying the one or more artificial intelligence techniques comprises passing the multiple determined parameters through at least one neural network. ### Claim 19 (depends on 17) The apparatus of claim 17, wherein applying the one or more artificial intelligence techniques comprises passing the multiple determined parameters through at least one artificial neural network multilayer perceptron. ### Claim 20 (depends on 17) The apparatus of claim 17, wherein performing the one or more automated actions comprises computing a confidence value attributed to the at least one generated delivery data prediction based at least in part on a level of complexity associated with the at least one data integration demand.