US 12,254,419 B2
Machine learning techniques for environmental discovery, environmental validation, and automated knowledge repository generation
Sastry V S M Durvasula, Phoenix, AZ (US); Neema Uthappa, Phoenix, AZ (US); Sriram Venkatesan, Princeton Junction, NJ (US); Sonam Jha, Short Hills, NJ (US); Jaspreet Singh, Fair Lawn, NJ (US); and Rares Almasan, Phoenix, AZ (US)
Assigned to MCKINSEY & COMPANY, INC., New York, NY (US)
Filed by MCKINSEY & COMPANY, INC., New York, NY (US)
Filed on Oct. 20, 2021, as Appl. No. 17/506,521.
Prior Publication US 2023/0117893 A1, Apr. 20, 2023
Int. Cl. G06N 5/022 (2023.01); G06F 9/50 (2006.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G06N 5/022 (2013.01) [G06F 9/5072 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for environmental discovery, environmental validation, and automated knowledge engine generation; comprising:
scanning an existing computing environment to collect data and architecture state corresponding to a current computing environment;
collecting, from a user via a causative questionnaire, data and architecture state corresponding to a future computing environment;
analyzing one or both of (i) the data and architecture state corresponding to the current environment, and (ii) the data and architecture state corresponding to the future environment using a diagnostic analytics machine learning model that processes inferences output by a descriptive analytics machine learning model and a predictive analytics machine learning model,
wherein the predictive analytics machine learning model predicts a frequency of updates to the computing environment and/or a volume of data to be updated in the computing environment, to generate a summary of a number of cloud deployment options for migrating the current computing environment to the future computing environment and one or more recommended actions,
wherein the diagnostic analytics machine learning model is trained to predict diagnostic analytics; and
causing the summary of the number of cloud deployment options and/or the recommended actions to be displayed in a computing device,
wherein the summary of the number of cloud deployment options and/or recommended actions includes a step-by-step visualization corresponding to the future computing environment, and
wherein the visualization includes at least one of a chart, a graph or a plot that depicts a nested hierarchical view describing one or both of (i) the current computing environment, and (ii) the future computing environment.