# US 12,118,385 B2 · System and method for real-time data dependency management and task orchestration > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,118,385 B2 - Document ID: US12118385B2 - Status: Granted - Kind: B2 - Application number: 17/649,608 - Filed: 2022-02-01 - Published: 2023-08-03 - Granted: 2024-10-15 - Earliest claimed: 2022-02-01 - Assignees: JPMorgan Chase Bank, N.A. - Applicants: JPMorgan Chase Bank, N.A. - Inventors: Chandra Gorantla; Kevin Fung - Web page: https://patentgrep.com/patent/US12118385B2 ## CPC - G06F 9/4881: {Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Various methods, apparatuses/systems, and media for real-time data dependency management are disclosed. A processor extracts data entity events from a plurality of data sets from upstream application; identifies dependent data entities for each data entity event based on initializing a data dependency graph with parent data nodes that represent all entities and their respective child data dependencies; publishes a data dependency event for each required parent data node in the data dependency graph; publishes a data dependency ready event for a certain parent node based on determining the certain parent node is configured for event publishing and that the certain parent node's child data dependencies are available; transmits the data dependency ready event to a task orchestration service platform; and orchestrates, upon receiving the data dependency ready event by the task orchestration service platform, a process instance and executes tasks for a corresponding data entity based on the process instance. ## Claims ### Claim 1 A method for real-time data dependency management by utilizing one or more processors along with allocated memory, the method comprising: receiving a plurality of data sets from a plurality of upstream applications; extracting data entity events from the plurality of data sets; identifying dependent data entities for each data entity event based on initializing a data dependency graph with parent data nodes that represent all entities and their respective child data dependencies; publishing a data dependency event to an inbound topic of a data dependency service platform for each required parent data node in the data dependency graph; publishing a data dependency ready event for a certain parent node based on determining that the certain parent node is configured for event publishing and that the certain parent node's child data dependencies are available; transmitting the data dependency ready event to a task orchestration service platform; and orchestrating, upon receiving the data dependency ready event by the task orchestration service platform, a process instance and executing tasks for a corresponding data entity based on the process instance. ### Claim 2 (depends on 1) The method according to claim 1, wherein the plurality of data sets relate to margin management workflow and include one or more of the following data: trades data, internal reference data, initial margin data, and agreements data between parties. ### Claim 3 (depends on 1) The method according to claim 1, wherein the data dependency event includes data dependency state event that represents availability of a data dependency. ### Claim 4 (depends on 1) The method according to claim 1, wherein the data dependency event includes graph modification event that represents structural change in the data dependency graph. ### Claim 5 (depends on 1) The method according to claim 1, wherein the structural change in the data dependency graph includes one or more of the following events: adding a data dependency node; removing a data dependency node; and moving a child data dependency node to a different parent node. ### Claim 6 (depends on 1) The method according to claim 1, further comprising: displaying the process instance as a task graph with nodes that are sequential or parallel with forks, joins and rules for task transitions. ### Claim 7 (depends on 6) The method according to claim 6, further comprising: publishing events identifying what tasks to be executed, and wherein the task graph includes relationships among the tasks to identify what is dependent on what other task. ### Claim 8 A system for real-time data dependency management, the system comprising: a processor; and a memory operatively connected to the processor via a communication interface, the memory storing computer readable instructions, when executed, causes the processor to: receive a plurality of data sets from a plurality of upstream applications; extract data entity events from the plurality of data sets; identify dependent data entities for each data entity event based on initializing a data dependency graph with parent data nodes that represent all entities and their respective child data dependencies; publish a data dependency event to an inbound topic of a data dependency service platform for each required parent data node in the data dependency graph; publish a data dependency ready event for a certain parent node based on determining that the certain parent node is configured for event publishing and that the certain parent node's child data dependencies are available; transmit the data dependency ready event to a task orchestration service platform; and orchestrate, upon receiving the data dependency ready event by the task orchestration service platform, a process instance and execute tasks for a corresponding data entity based on the process instance. ### Claim 9 (depends on 8) The system according to claim 8, wherein the plurality of data sets relate to margin management workflow and include one or more of the following data: trades data, internal reference data, initial margin data, and agreements data between parties. ### Claim 10 (depends on 8) The system according to claim 8, wherein the data dependency event includes data dependency state event that represents availability of a data dependency. ### Claim 11 (depends on 8) The system according to claim 8, wherein the data dependency event includes graph modification event that represents structural change in the data dependency graph. ### Claim 12 (depends on 8) The system according to claim 8, wherein the structural change in the data dependency graph includes one or more of the following events: adding a data dependency node; removing a data dependency node; and moving a child data dependency node to a different parent node. ### Claim 13 (depends on 8) The system according to claim 8, wherein the processor is further configured to: display the process instance as a task graph with nodes that are sequential or parallel with forks, joins and rules for task transitions. ### Claim 14 (depends on 13) The system according to claim 13, wherein the processor is further configured to: publish events identifying what tasks to be executed, and wherein the task graph includes relationships among the tasks to identify what is dependent on what other task. ### Claim 15 A non-transitory computer readable medium configured to store instructions for real-time data dependency management, wherein, when executed, the instructions cause a processor to perform the following: receiving a plurality of data sets from a plurality of upstream applications; extracting data entity events from the plurality of data sets; identifying dependent data entities for each data entity event based on initializing a data dependency graph with parent data nodes that represent all entities and their respective child data dependencies; publishing a data dependency event to an inbound topic of a data dependency service platform for each required parent data node in the data dependency graph; publishing a data dependency ready event for a certain parent node based on determining that the certain parent node is configured for event publishing and that the certain parent node's child data dependencies are available; transmitting the data dependency ready event to a task orchestration service platform; and orchestrating, upon receiving the data dependency ready event by the task orchestration service platform, a process instance and executing tasks for a corresponding data entity based on the process instance. ### Claim 16 (depends on 15) The non-transitory computer readable medium according to claim 15, wherein the plurality of data sets relate to margin management workflow and include one or more of the following data: trades data, internal reference data, initial margin data, and agreements data between parties. ### Claim 17 (depends on 15) The non-transitory computer readable medium according to claim 15, wherein the data dependency event includes data dependency state event that represents availability of a data dependency and graph modification event that represents structural change in the data dependency graph. ### Claim 18 (depends on 15) The non-transitory computer readable medium according to claim 15, wherein the structural change in the data dependency graph includes one or more of the following events: adding a data dependency node; removing a data dependency node; and moving a child data dependency node to a different parent node. ### Claim 19 (depends on 15) The non-transitory computer readable medium according to claim 15, wherein, when executed, the instructions further cause the processor to perform the following: displaying the process instance as a task graph with nodes that are sequential or parallel with forks, joins and rules for task transitions. ### Claim 20 (depends on 19) The non-transitory computer readable medium according to claim 19, wherein, when executed, the instructions further cause the processor to perform the following: publishing events identifying what tasks to be executed, and wherein the task graph includes relationships among the tasks to identify what is dependent on what other task.