Abstract: In one example, a network management system (NMS) device manages a plurality of network devices. The device includes a memory configured to store data representing a data model for a plurality of network devices managed by the NMS, and one or more processors configured to retrieve data representing the data model, construct a GraphQL model having a plurality of nodes, each of the nodes corresponding to one of the network devices according to the data model store data representing properties of the network devices associated with corresponding nodes of the GraphQL model according to the data model, receive a GraphQL query including data representing at least one query property, determine which of the nodes has a property matching the at least one query property, and return data identifying which of the network devices corresponds to the nodes having the property matching the at least one query property.

Abstract: An artificially intelligent system for generating compliance-related content, the system includes monitoring circuitry that receives regulatory compliance data from published regulatory texts; a taxonomy engine that generates taxonomy-based classifications of the regulatory compliance data, the taxonomy-based classifications having a plurality of modules and compliance requirements within each module.

Abstract: A method for generating a model for recommendations from an item data set for a target data set includes embedding a set of targets from the target data set in a shared coordinate space using a first embedding function, embedding a first set of items from the item data set in the shared coordinate space using a second embedding function, selecting at least one target from the set of targets, and identifying a second set of items from the first set of items that are proximate to the at least one target as candidates from the recommendations.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving, at a clustered filesystem from a formatted filesystem, a request to perform a data integrity check for a portion of data. A determination is made as to whether the request includes a filesystem type of the portion of data, and in response to determining that the request includes a filesystem type of the portion of data, another determination is made as to whether the clustered filesystem supports the data integrity check for the filesystem type. In response to determining the clustered filesystem supports the data integrity check, another determination is made as to whether the portion of data is currently available. Furthermore, the computer-implemented method includes causing the data integrity check to be performed in response to determining that the portion of data is currently available. Results of performing the data integrity check are also sent to the formatted filesystem.

Abstract: A system and method for improving a predictive accuracy of a machine learning-based virtual conversational agent that includes computing an antecedent context nexus based on query embeddings computed for a preceding query input by a user, wherein the antecedent context nexus includes a pairing of a categorial parameter and a sub-categorical parameter derived based on the query embeddings of the preceding query; creating search logic parameters based on the categorical parameter and the sub-categorical parameter of the antecedent context nexus; executing a context nexus-informed search of a corpus of structured data using at least the search logic parameters; extracting a response candidate from the corpus of structured data based on the execution of the context nexus-informed search; constructing a response to the preceding query based on the extracted response candidate; and returning, via a user interface, the response to the preceding query.

Abstract: A method implementing a fault-tolerant data warehouse using availability zones includes allocating a plurality of processing units to a data warehouse, the processing units located in different availability zones, an availability zone comprising one or more data centers. The method further includes routing a query to a processing unit within the data warehouse, the query having a common session identifier with a query previously provided to the processing unit, the processing unit determined to be caching a data segment associated with a cloud storage resource independent of the plurality of processing units. The method further includes, as a result of monitoring a number of queries running at an input degree of parallelism, determining that the processing capacity of the processing units has reached a threshold; and changing a total number of processing units using the input degree of parallelism and the number of queries.

Abstract: A method includes receiving a plurality of files where each file represents an object. The method further combines selected files of the plurality of files into an aggregation file and stores the aggregation file on low-latency storage media, such as disk storage media. The method represents the aggregation file with a single inode that is stored on the low-latency storage media. The method migrates the aggregate file to high-latency storage media, such as tape storage media, while leaving the single inode representing the aggregation file on the low-latency storage media. By collecting files into larger aggregation files, the number of files archived is significantly reduced and the files archived are of larger size. The reduced number of files and increased size of the files improves archival and retrieval performance due to reduced metadata operation overhead. A corresponding system and computer program product are also disclosed.

Abstract: Systems, methods, and graphical user interfaces (GUIs) for ingesting and enriching data regarding a plurality of entities are provided. A first data set comprising company data and a second data set comprising customer data are ingested. The first data set is processed to generate a processed data set. The first data set may be processed by applying an entity matching technique, wherein one or more data elements are generated based on whether an entity of the first data set and an entity of the second data set are commonly associated. The first data set may additionally or alternatively be processed by applying a statistical matching technique, wherein one or more predicted data elements are generated based on similarity between an entity of the first data set and one or more entities of the second data set.

Abstract: Techniques of data flow control are disclosed herein. One example technique includes upon receiving a notification indicating a change to a content item in a source shard, parsing the content item to extract data representing attributes of the content item and identifying a partition of the system-wide index based on the extracted data representing the attributes of the content item. The example technique can also include transmitting, to a token issuer, a request for a token that represents a permission to write to the identified partition of the system-wide index and upon receiving a token issued by the token issuer in response to the transmitted request, transmitting the extracted data representing the attributes of the content item along with the received token to write the extracted data in the partition of the system-wide index.

Abstract: A system is described that includes an electronic program guide (EPG) data receiver and a media content catalog enhancer. The EPG receiver is configured to receive EPG data from an EPG data provider. The media content catalog enhancer is configured to determine that an item of media content identified by the EPG data comprises new media content and, in response to determining that the item of media content identified by the EPG data comprises new media content, to cause a web crawler to crawl a source website associated with the new media content to obtain information about the new media content and to store the obtained information about the new media content in a database, the database comprising a catalog of media content that is searchable by an end user to identify and access content for playback via an end user device.

Abstract: There is provided a data processing apparatus including a processor, the processor is configured to: receive one or more sets of data output from at least one data output apparatus via a communication network, each set of the data including sensor data obtained by at least one sensor and first specifying information that specifies the data processing apparatus; determine whether or not the first specifying information included in the received one or more sets of data satisfies a predetermined condition; classify the one or more sets of data determined to satisfy the condition into a same group; and generate and output an output file based on the one or more sets of data classified into the same group.

Abstract: Automated query retry includes selecting a first node of a plurality of nodes of an execution platform in response to a query. The first node is configured with a first version of a database platform. A first execution of the query is performed using the first version of the database platform at the first node. The method further includes detecting the first execution results in a failed execution. A second execution of the query is scheduled. The second execution uses at least one of the first version of the database platform or a second version of the database platform configured at a second node of the plurality of nodes. The second version is released after the first version. A cause of the failed execution of the query at the first node is determined based at least in part on a result of the second execution of the query.

Abstract: Provided are methods and systems comprising determining one or more relationships between a plurality of data sets, determining a score for each of the one or more relationships, generating a graphical data set object for each of the plurality of data sets, classifying each graphical data set object as connected or unconnected based on the score for each of the one or more relationships, generating a graphical connector object between connected graphical data set objects, and outputting the connected graphical data set objects with corresponding graphical connector objects and the unconnected graphical data set objects.

Abstract: A method includes defining a set of context types; defining a set of source types, each comprising context types; defining, for each source type, and for each context type included in the events from data sources having the source type, a context definition comprising a set of fields, in events from the data sources, that are associated with the context type; receiving a query comprising a first field value and a time period; retrieving a plurality of events that include the first field value and the time period; for each retrieved event, and for each context definition defined for a source type and a context type of a data source from which the retrieved event originated, determining field values of fields in the set of fields of the context definition; aggregating, for each context type, determined field values from the events; and generating an output.

Abstract: A computer-implemented method enables workload scheduling in a storage system for optimized deduplication. The method includes determining dynamic correlations of deduplications between workload processes in a prior time window. Workload processes include one or more tasks with defined execution timing parameters. The method further includes determining deduplication ratios based on the correlations of the deduplications between the workload processes. The method further includes scheduling multiple workload processes based on a highest determined deduplication ratio of the determined deduplication ratios.

Abstract: A computerized-method for scaling automatic deployment of a machine-learning detection model in a cloud-based managed analytics service by knowledge sharing to overcome an imbalanced dataset learning problem. The computerized-method includes: sending the received data to machine-learning models to synthesize patterns of the received data to yield a differential privacy data; maintaining in the database the differential privacy data of one or more on-prem cloud-based managed analytics services to generate a consortium shared synthetic data lake; operating phases of machine-learning detection model based on the received data and data in the database to create a packaged model. The data in the database is aggregated and used during the operating phases of the machine-learning detection model to create a packaged model for other on-prem cloud-based managed analytics services, thus overcoming imbalanced dataset learning thereof, and after the packaged model is created it is automatically deployed on-prem.

Abstract: Systems and methods for creating a live copy of a data object from a production system for use by third party applications. The systems and methods include receiving at least one request for a copy of production data from an application; creating a live backup copy; creating a flash copy of the live backup copy, and a flash copy bitmap; creating a modified version of the live backup copy by changing a subset of data in the live backup copy; recording the changed subset of data using the flash copy bitmap; mounting, the modified version of the live backup copy to the application; and transforming the modified version of the live backup copy back to the live backup copy when unmounting the modified version of the live backup copy of the production data from the application by applying changes associated with the flash copy bitmap to the live backup copy.

Abstract: Disclosed herein are systems and method for providing a File System (FS) without redundancy for one or more services. In one aspect, an exemplary method comprises, mounting a base image of microservices to a directory, for each of the one or more services, union-mounting a service image on top of the base image, identifying all dependencies associated with the service image, and creating one or more sub-directories for each dependency associated with the service image, for each identified dependency, creating a link between the dependency and the union-mounted service image and base image, and creating, one or more micro-services.

Abstract: Indexing a data corpus to a set of multidimensional points, including: generating a set of points in a multidimensional space; identifying, for each sample in a plurality of samples in a data corpus, a nearest point in the set of points; and generating an index mapping each sample with the nearest point in the set of points.

Abstract: A computer-implemented method comprising receiving, from a user computer at a server computer, a configuration file specifying one or more data source identifiers of source database tables in a target database system, one or more data sink identifiers of sink database tables in the target database system, and two or more data transformations; the server computer initiating execution of a data transformation framework by loading one or more configuration parameters of the configuration file into main memory of the server computer to define a workflow; creating and storing a configuration table based on the configuration file, the configuration table comprising a plurality of dynamic queries, a plurality of identifiers of transformation functions, and names of the one or more data transformations; in the configuration table, for each of the transformations, creating a plurality of dynamic common table expression queries, each of the dynamic common table expression queries being associated with a particular tran