Abstract: The present invention provides a method including receiving a data set for an entity including data associated with criterions. Each of the data entries is grouped into a grouping. Then generating an error probability for the grouping. The error probability includes an ensemble of algorithms that each provide an indication of a potential error within the grouping. Also, generating a flow metric for the grouping by evaluating a magnitude of values for the data entries of the grouping. Then determining a materiality factor for each grouping using the flow metric for the grouping, a planned materiality threshold, and a performance materiality and generating a risk of material error for the grouping using the error probability and the materiality factor of the grouping. Also, highlighting a grouping within the data set based on the risk of material error of the grouping.

Abstract: Some embodiments provide a program that determines a plurality of data objects. Each data object in the plurality of data objects includes a first attribute and a second attribute. The program further sorts values of the first attribute of the plurality of data objects. The program also sorts values of the second attribute of the plurality of data objects. The program further determines a first distance value based on the sorted values of the first attribute of the plurality of data objects. The program also determines a second distance value based on the sorted values of the second attribute of the plurality of data objects. The program further defines a plurality of clusters based on the sorted values of the first attribute of the plurality of data objects, the first distance value, the sorted values of the second attribute of the plurality of data objects, and the second distance value.

Abstract: Various embodiments are provided herein for systems and methods for real-time, or near real-time, multi-dimensional ranking of experts. In at least one embodiment, receiving one or more evaluation datasets; for each given evaluation dataset, associating the evaluation dataset with: (i) at least one evaluation data category, (ii) at least one taxonomy category, and (iii) at least one expert of the plurality of experts; subsequently, receiving one or more search filter criteria for ranking at least a subset of the plurality of experts; generating a ranking of the at least subset of the plurality of experts, wherein the ranking is based on the search filter criteria, and is further generated based on the associations determined for each evaluation dataset; and displaying, on a user interface, at least a portion of the plurality of rankings as the multi-dimensional ranking of the plurality of experts.

Abstract: Techniques for multi database query processing are described. Objects located in a plurality of databases referenced in a query can be compiled. A connection string based on the compiled objects can be generated. The connection string can include mapping information related to the related to the plurality of databases and cluster information of where the plurality of databases are stored in the network-based data system. The connection string can then be included in a query plan to allow for execution of the query plan using the connection string to access the objects in the plurality of databases.

Abstract: In some implementations, a device may receive data associated with a set of taxonomies, wherein a taxonomy, of the set of taxonomies, represents a classification of a set of relationships of data entries of the data. The device may integrate the set of taxonomies to generate a meta-taxonomy of the data. The device may generate a data graph of the data based on integrating the set of taxonomies to generate the meta-taxonomy, wherein the data graph is based on a graph-based search model that is associated with at least one of: taxonomy-based filtering, metadata attribute prioritization, or semantic matching. The device may store the data graph.

Abstract: A data processing system and corresponding method are presented. The system includes a communication module to retrieve a first document and a second document; a first database to store the first and second documents; and a processor. The processor extracts first data from the first document, orders the first data into a first data structure using a set of translation tables. The processor also extracts second data from the second document, orders the second data into a second data structure using the set of translation tables. The first data structure and the second data structure have a first and a second format, respectively. The first data and the second data comprise a plurality of entities, and the processor is configured to compare entities from the first data structure and the second data structure to identify matching entities.

Abstract: Disclosed are a method and device for managing a project by using data merging. A project is efficiently operated by dividing a project based on a minimum unit task and designing a plurality of child projects connected in sequential order such that a plurality of child projects proceed in order.

Abstract: A system and method for an online transaction system to transition from operating under a first mode (FM) to operating under a second mode (SM), and vice versa. In the FM, transaction nodes identify transactions with sequential numbers obtained from a global transaction server (GTS). In the SM, transaction nodes identify consecutive transactions with timestamps based on global clock servers (GCSs). When transitioning from one mode to the other mode, a controller instructs the transactions nodes to provide GCS-based transaction timestamps and error bounds to the GTS, which modifies the timestamps and the error bounds based on previously received timestamps and error bounds, and on the latest transaction number issued by the GTS. Modified timestamps and error bounds are obtained at the transaction nodes. Each transaction is timestamped with its respective modified timestamp. But there is a delay equal to the modified error bound before requesting another modified timestamp.

Abstract: A non-transitory computer-readable recording medium stores therein a data clustering program that causes a computer to execute a process. The process includes calculating, for each of plural points included in a set of point group data, an eigenvector by using principal component analysis for a set of point group data that is present within a predetermined distance from a point; calculating a curvature of a multidimensional function having an extreme point that is a point positioned nearest to the eigenvector calculated; executing, on the basis of the curvature for each of the plural points of the set of point group data, clustering of the plural points; and outputting a result of execution of the clustering.

Abstract: An information handling system may include at least one processor and a non-transitory memory coupled to the at least one processor. The information handling system may be configured to: transmit a request to a remote information handling system regarding an upcoming cluster scaling event for an information handling system cluster; receive information from the remote information handling system indicative of a plurality of known-good cluster configurations; determine a closest one of the plurality of known-good cluster configurations; make one or more configuration changes to the information handling system cluster to cause a configuration of the information handling system cluster to match the closest one; and initiate the cluster scaling event.

Abstract: A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues with the plurality of components. The data is analyzed and categorized based at least in part on the analysis. In the method, one or more application programming interfaces (APIs) are selected to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the categorization of the data, and the data is pushed to the one or more APIs.

Abstract: The present disclosure relates to a digital asset synchronization system that provides improved local and remote synchronization of digital assets. In particular, the digital asset synchronization system manages digital assets by separating each digital asset into multiple components stored as a set of distributed individual files. Employing individual components for a digital asset rather than single monolithic file enables the digital asset synchronization system to provide safe concurrent access to the digital asset from multiple applications on the same device and across different devices. In addition, using components for a digital asset provides the digital asset synchronization system with the ability to efficiently store and synchronize multiple versions of the digital asset, both locally and remotely.

Abstract: The subject technology selects a particular zone among multiple zones based on a target skew to meet a global balancing of cluster instances. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determines a respective number of cluster instances. The subject technology identifies a second particular type of cluster instance to add based on a total number of the second particular type of cluster instance in the multiple zones and a second total number of the particular type of cluster instance in the multiple zones. The subject technology adds the second particular type of cluster instance to a second particular zone to meet the global balancing of cluster instances in the multiple zones.

Abstract: Techniques for implementing user interfaces, systems, and processes for multidimensional clustering and analysis are described herein. In one aspect, an application or cloud service receives a request to cluster a set of records where the request identifies a first set of one or more dimensions to use for clustering and a second set of one or more dimensions to analyze for correlation patterns. Responsive to receiving the request to cluster the set of records, the system generates clusters based at least in part on variances in the first set of one or more dimensions, wherein each cluster includes at least one record from the set of records. The system may generate, for each respective cluster, an analytic result that identifies how strongly the second set of one or more dimensions correlate to the respective cluster. The system may present the clusters and analytic results for further processing.

Abstract: A method is provided for classifying a maintenance record for a machine. The method includes receiving the maintenance record including maintenance event information expressed as a collection of terms of interest, and normalizing the terms of interest to their non-abbreviated, dictionary form. The method includes accessing a database of authoritative engineering information from electronic documents, expressed textually and indexed by class of a plurality of classes. The method includes weighted scoring the authoritative engineering information that uses one or more of the terms of interest represented in the weighted scoring by uniqueness scores. Matching authoritative engineering information is determined for the maintenance event information based on the weighted scoring, and the maintenance record is labeled with the class to which the matching authoritative engineering information is indexed.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include an atomized workflow loader configured to receive an atomized dataset to load into a data store, and to determine resource requirements data to describe at least one resource requirement. The atomized workflow loader may be further configured to select a data store type based on a resource requirement, and perform a load operation of the atomized dataset as a function of the data store type.

Abstract: Large numbers of files having widely varying structures and formats may be ingested, and used to generate dynamic slot indexes that enable fast and reliable searching of the files. Unique data patterns within the files are used to generate unique pattern models, which enable model-specific mappings of file fields to slots of a dynamic slot index. Accordingly, the dynamic slot indexes may reuse a single slot for multiple fields. Complex queries may then be processed in a time-efficient and resource-efficient manner, even when rapidly ingesting huge numbers of files having indeterminate data patterns from many different sources.

Abstract: A method and a system for clustering executable files are provided. The method comprises: obtaining a plurality of executable files; for each executable file: (i) detecting repeat sequences of commands of a predetermined length in a given executable file; (ii) determining at least one frequently occurring sequence of the repeat sequences in the given executable file; and based on the at least one frequently occurring sequence of commands, attributing the given executable file to a respective family; iteratively executing the detecting, the determining, and the attributing until one of: all of the plurality of executable files are attributed to at least one respective family, and until un-attributed files of the plurality of executable files do not contain any repeat sequences of commands; and responsive to presence of un-attributed files, attributing each of the un-attributed files of the plurality of executable files to a separate family.

Abstract: A system and a method for contextual categorization of data comprises a server having a processor and a non-transitory computer-readable storage medium in electronic communication with the processor and comprising program instructions executable by the processor to access an initial inventory of data set and metadata associated with the initial inventory of data set. The system is then configured to classify the initial inventory of data set by using the metadata into (a) reduced set of data comprising high level sensitivity classification and (b) a remainder data set.

Abstract: The present disclosure relates to restricting electronic activities from being linked with record objects. According to at least one aspect of the disclosure, a method can include accessing, by one or more processors, a plurality of electronic activities, accessing a plurality of record objects of one or more systems of record, identifying an electronic activity of the plurality of electronic activities to match to one or more record objects, determining a data source provider associated with providing access to the electronic activity, and identifying a system of record corresponding to the determined data source provider. The system of record can include a plurality of candidate record objects to which to match the electronic activity. The method can include restricting the electronic activity from being linked with the at least one record object.