Abstract: An example computing system includes: a memory storing a plurality of data assets; and a processing system of an enterprise, the processing system comprising one or more processors implemented in circuitry, the processing system being configured to: maintain a plurality of data domains, each of the data domains being managed by an executive of the enterprise, and each of the domains having one or more subdomains; maintain the one or more subdomains of each of the plurality of data domains, each of the plurality of data domains being associated with one or more data use cases, one or more data sources, and one or more risk accessible units; and track defects of the data assets in each of the plurality of data domains.

Abstract: A computer-implemented method includes a processing node sending a request that includes an identified alert record from a shared alert data store that is shared amongst a cluster of processing nodes including the processing node. The processing node receives, responsive to the request, a delete alert record uniquely identifying the identified alert record and including an annotation identifying a new delete alert record as being a delete alert record type. The processing node matches, responsive to the annotation, the delete alert record to a local copy of the identified alert record based on the delete alert record uniquely identifying the identified alert record. The processing node deletes, based on the annotation, the local copy of the identified alert record according to the delete alert record.

Abstract: Exemplary embodiments can identify the toxic PI combinations and flag these combinations for evaluation. Because organization policies on toxic PI combinations can constantly evolve, the system may be continuously updated with the latest policies. Exemplary embodiments may be used as part of an automated code review for application development and for monitoring of existing applications and programs. Thus, exemplary embodiments take the guesswork out of identifying risks in applications and programs by providing an automated tool that can scan and identify toxic combinations in accordance with various policies.

Abstract: A first processing node of a cluster of processing nodes issues a first alert when first event data satisfies a trigger condition, and sends, to an alert data store external to the cluster, a first alert record of the first alert and suppression information based at least in part on the first alert. A second processing node of the cluster determines that second event data satisfies the trigger condition, obtains, from the alert data store, the suppression information indicating that an expiration time for suppressing the first alert is unexpired, and sends, to the alert data store, a second alert record of a second alert without issuing the second alert.

Abstract: A set of alert records stored in a shared alert data store that is shared amongst a cluster of processing nodes are presented in an interface. From the interface, a request is received to delete an identified alert record from the set of alert records. A delete alert record matching the identified alert record is added to the shared alert data store. The identified alert record is deleted from the shared alert data store responsive to the request. The delete alert record is transmitted to a processing node of the cluster of processing nodes, wherein the processing node deletes a local copy of the identified alert record according to the delete alert record.

Abstract: Artifact life tracking storage techniques include performing an artifact request of an artifact at an artifact storage node. A current time to live (TTL) value is identified. A determination is made whether to increment a TTL flag of the artifact. Responsive to determining that the TTL tag should be incremented, the TTL flag is incremented to a subsequent value in a TTL extender list. Responsive to incrementing the TTL tag, the TTL modified tag value is set to the current time value.

Abstract: A computing system is configured to generate a data model comprising data sources, data use cases, and data governance policies retrieved from one or more data platforms via one or more platform and vendor agnostic APIs, wherein the data sources, data use cases, data governance policies, and APIs are aligned to one or more data domains. The computing system is further configured to create, based identifying information from the one or more data sources, a data linkage between a data source, a data use case, a data governance policy, and a data domain. The computing system is further configured to determine, based on the data governance policy and quality criteria, the level of quality of the data source. The computing system is further configured to generate, based on the level of quality of the data source, a report indicating the status of the data domain and data use case.

Abstract: An embodiment of the present invention is directed to implementing machine learning to define business logic and lineage. The system analyzes data patterns of SORs as well as consumption attributes to define the business logic. An embodiment of the present invention may achieve over 95% match rate for complex attributes. When provided with thousands of SOR attributes, the innovative system may identify a handful of relevant SOR attributes required as well as the business logic to derive the consumption attribute.

Abstract: A first processing node of a cluster of processing nodes issues a first alert when first event data satisfies a trigger condition, and sends, to an alert data store external to the cluster, a first alert record of the first alert and suppression information based at least in part on the first alert. A second processing node of the cluster determines that second event data satisfies the trigger condition, obtains, from the alert data store, the suppression information indicating that an expiration time for suppressing the first alert is unexpired, and sends, to the alert data store, a second alert record of a second alert without issuing the second alert.

Abstract: Artifact life tracking storage techniques include performing an artifact request of an artifact at an artifact storage node. A current time to live (TTL) value is identified. A determination is made whether to increment a TTL flag of the artifact. Responsive to determining that the TTL tag should be incremented, the TTL flag is incremented to a subsequent value in a TTL extender list. Responsive to incrementing the TTL tag, the TTL modified tag value is set to the current time value.

Abstract: Exemplary embodiments can identify the toxic PI combinations and flag these combinations for evaluation. Because organization policies on toxic PI combinations can constantly evolve, the system may be continuously updated with the latest policies. Exemplary embodiments may be used as part of an automated code review for application development and for monitoring of existing applications and programs. Thus, exemplary embodiments take the guesswork out of identifying risks in applications and programs by providing an automated tool that can scan and identify toxic combinations in accordance with various policies.

Abstract: An embodiment of the present invention is directed to configuring optimal parallelism on Hadoop processes at specific processing points for improved performance and throughput. An embodiment of the present invention forces Hadoop into high parallelism independent of a HDFS file size. An embodiment of the present invention achieves an order of magnitude improvement in performance and data throughputs to meet the SLAs. An embodiment of the present invention provides a design pattern unique to distributed processing in Hadoop to accomplish the required data throughputs for the CDC process.

Abstract: Exemplary embodiments can identify the toxic PI combinations and flag these combinations for evaluation. Because organization policies on toxic PI combinations can constantly evolve, the system may be continuously updated with the latest policies. Exemplary embodiments may be used as part of an automated code review for application development and for monitoring of existing applications and programs. Thus, exemplary embodiments take the guesswork out of identifying risks in applications and programs by providing an automated tool that can scan and identify toxic combinations in accordance with various policies.

Abstract: An embodiment of the present invention is directed to implementing machine learning to define business logic and lineage. The system analyzes data patterns of SORs as well as consumption attributes to define the business logic. An embodiment of the present invention may achieve over 95% match rate for complex attributes. When provided with thousands of SOR attributes, the innovative system may identify a handful of relevant SOR attributes required as well as the business logic to derive the consumption attribute.

Abstract: An embodiment of the present invention is directed to creating a re-usable code component that may be used with the data manipulation and transformation tool to natively support DML functionality. In addition to Insert, Update, and Delete, an addition function directed to “DeDup” may be implemented as it is used frequently in data transformation processes. An embodiment of the present invention is directed to capability to roll-back to a prior version of the original dataset. Any number of versions as required may be maintained.

Abstract: An embodiment of the present invention is directed to implementing machine learning to define business logic and lineage. The system analyzes data patterns of SORs as well as consumption attributes to define the business logic. An embodiment of the present invention may achieve over 95% match rate for complex attributes. When provided with thousands of SOR attributes, the innovative system may identify a handful of relevant SOR attributes required as well as the business logic to derive the consumption attribute.

Abstract: A hybrid vehicle includes an isolation switch disposed between a first bus that is electrically coupled to a starter for an engine and a second bus that is electrically coupled to a power converter and accessory loads. The hybrid vehicle includes a controller programmed to normally command the switch closed, and, in response to expiration of a predetermined time interval without starting the engine, command the switch to open for a predetermined duration to perform diagnostics on the isolation switch.

Abstract: Exemplary embodiments can identify the toxic PI combinations and flag these combinations for evaluation. Because organization policies on toxic PI combinations can constantly evolve, the system may be continuously updated with the latest policies. Exemplary embodiments may be used as part of an automated code review for application development and for monitoring of existing applications and programs. Thus, exemplary embodiments take the guesswork out of identifying risks in applications and programs by providing an automated tool that can scan and identify toxic combinations in accordance with various policies.

Abstract: An embodiment of the present invention is directed to automating deployment into tools and technologies related to big data analytics. The innovative system automates deployment and integration of various data related tools and technologies while managing internal applications and processes for change management. Deployment generally refers to implementation of code into the production environment. The innovative system integrates with an entity's Change Management Tools and Processes (e.g., ITSM, AIM, GFS, etc.) to provide automated deployment.

Abstract: The invention relates to implementing a test data tool that generates test data based on production data patterns. According to an embodiment of the present invention, the test data tool comprises: a processor configured to: receive, via the data input, production data from the one or more production environments, the production data comprises personally identifiable information; identify a plurality of attributes from the production data; for each attribute, identify one or more data patterns; generate one or more rules that define the one or more data patterns for each attribute; generate a configuration file based on the one or more rules; apply the configuration file to generate test data in a manner that obscures personally identifiable information existing in the production data; and transmit the test data to a UAT environment.