Abstract: A system and method for providing an improved user interface for executing data operations. A method includes: identifying a first node and a second node from different connections graphs, each node representing a respective user account, the user accounts of the first and second nodes sharing at least one common attribute; generating, based on the different connections graphs, an influence indicator for each of the first node and the second node; identifying a data operation executed by the first node on a dataset when the influence indicator of the first node is higher than the influence indicator of the second node, wherein the identified data operation causes generation or retrieval of business intelligence system data when executed; and sending data indicating the identified data operation to a device of the second node, wherein the device is configured to display a user interface including the identified data operation.

Abstract: A data lineage system tracks performance of data flows through different transformations independent of the systems that perform the transformations. A data flow model is maintained as a graph in the data lineage system that is updated by data processors to include performance history of different transformations in the data flow. Subsequent analyses of the data flow model, such as tracing particular data, can be supported using the recorded performance information in the graph of the data flow model.

Abstract: Annotating content, comprising data values of one or more tags corresponding to a process device within a continuous process, with content descriptors in a historian system. Content descriptors enable indexing and saving content within a search service database for later retrieval by search strings that match the content descriptors. Content having one or more common content descriptors are retrieved and transmitted to a client computing device via a communications network for displaying in a dashboard on the client computing device.

Abstract: In embodiments, at a first cluster, information identifying a plurality of indexers of the first cluster is determined based on a master node of the first cluster identifying active indexers within the first cluster. The information is transmitted from the first cluster to a second cluster. Such information can include a list of active indexers, and an indication of how to communicate with the plurality of indexers that is used by the second cluster in distributing a distributed search query. The distributed search query is received at the plurality of indexers of the first cluster. The distributed search query is distributed across the plurality of indexers based on the information identifying the plurality of indexers. A response is provided from at least one of the plurality of indexers, wherein each response from a respective indexer is generated based on an evaluation of the distributed search query.

Abstract: Methods for analyzing data are disclosed. One disclosed method includes defining an intent language model for domain specific meaning behind historical enterprise data produced during operation of an enterprise; applying the historical enterprise data to build the intent language model; extracting intent element features of interest from the enterprise data to generate domain specific intent metadata; and storing the domain specific intent metadata into a database. The historical enterprise data includes findings and observations by one or more human experts in one or more service records and data associated with a problem.

Abstract: A system is provided for resolving data errors. The system is configured to obtain an erroneous data element received from a source system and generate a plurality of probable data values for the data element. For each probable data value of the plurality of probable data values, the system verifies whether the probable data value can be processed successfully by an Extract, Transform and Load (ETL) logic and by one or more target applications configured to process the data element. The system determines one of the probable data values as a suggested data value of the data element, based on the verification of the probable data values. The system outputs the suggested data value for processing by the ETL logic.

Abstract: Techniques are provided for autonomous caching of hierarchical data. In one technique, query log data is stored that comprises multiple entries, each entry (a) corresponding to a different instance of a query that was executed against a database and (b) indicating a tuple (or level grouping) comprising a set of hierarchy levels corresponding to a set of dimensions. Multiple tuples indicated in the query log data are identified. For each tuple: (1) a set of entries that indicate the tuple is identified and the set of entries is associated with the tuple; (2) aggregated performance data is generated for the tuple based on performance data associated with each entry in the set of entries that is associated with the tuple; and (3) based on the aggregated performance data, it is determined whether to create a new auto-cache table or to delete an existing auto-cache table associated with the tuple.

Abstract: Methods, servers, and computer programs for processing multiple data records in response to a database request with search indications are provided. The server retrieves multiple data records with parameter values in the fields which correspond to the search indications indicated by the database request, determines weight values for at least two of the fields based on the corresponding parameter values of the at least two fields, calculates an aggregated score for at least a number of the retrieved data records based on the determined weight values, and returns at least a subset of the retrieved data records to the client based on the calculated aggregated scores.

Abstract: Described is a system for rule-based re-tiering of backup data stored on a cloud-based object storage. More specifically, the system may re-tier objects based on one or more storage rules such that the system retains the ability to efficiently perform a full restore of backup data even when incremental backups are performed to a cloud-based object storage. To provide such a capability, the system may maintain a specialized metadata database that stores information indicating the backup time for each backup, and a list of objects required to perform a full restore to each of the backup times. Accordingly, when initiating a re-tiering based on one or more storage rules, the system may intelligently select candidate objects for re-tiering by leveraging the metadata database to ensure that objects that may still need to be referenced are not unnecessarily moved to a lower storage tier.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a sparse mapping of a data hierarchy. In one aspect, a method includes accessing a data hierarchy of elements, receiving a list of identifiers that each identify an element in the data hierarchy; determining, from the data hierarchy and the list of identifiers, a minimum tree that includes each of the identified elements identified by the list of identifiers additional elements that are not identified by the list of identifiers, where the identified elements and the additional elements define a set of a minimum number of elements necessary to form a path in the data hierarchy that connects all of the identified elements identified by the list of identifiers, and where the elements that belong to the minimum tree are a proper subset of elements of the data hierarchy.

Abstract: In one embodiment, the present invention is directed to a method implemented on a computer system of database retrieval including organizing and suggesting search results by style, not just product category. In one embodiment, a computer implemented smoothing algorithm is used to adjust the ranking feature calculations from insufficient data. The use of smoothing improves the statistical confidence of the ranking features, creating a product ranking that is robust to small sample bias.

Abstract: Systems herein allow a user device to monitor calendar events with a secure bubble application. When an event is upcoming, the secure bubble application can present a notification. The secure bubble application can search other managed applications for content relevant to the meeting event. The secure bubble application can extract text, tags, and other metadata from the calendar event and any attached files. The text, tags, and other metadata can be used to search each managed application. Relevant emails, files, and notes can be displayed in a card generated by the secure bubble application.

Abstract: A document of written content may be obtained. The document may be a candidate for inclusion in a corpus. A first entity associated with the document may be identified. A first discrete entity associated with the first entity may be identified. The relationship associated with the first entity and the first discrete entity may be analyzed. Based on the analyzing, a likelihood that the document contains content that would be detrimental for inclusion in the corpus may be determined.

Abstract: One example method includes receiving a group of files, two or more of the files being of different respective file types, creating a backup saveset that includes the group of files, classifying each of the files in the backup saveset based in part on the respective file types of the files, assigning a respective storage media type to each of the classified files in the backup saveset, and transmitting the backup saveset to a storage site.

Abstract: The disclosed technologies are capable of selectively using data structure operations for path query evaluation. One technique involves reading a query that traverses at least two nodes and at least one edge of a graph in a graph database; compiling the query into a set of variables and a set of constraints, where the set of variables and the set of constraints correspond to the two nodes and the one edge of the graph; creating an in-memory data structure that comprises a table; using the set of variables and the set of constraints to determine an operation that is performable using the in-memory data structure; checking for an existence of a condition relating to the in-memory data structure or the operation; skipping the operation if the condition exists or executing the operation if the condition does not exist; and storing a set of intermediate query results in the table.

Abstract: Provided are techniques for role reversal of primary and secondary sites with minimal replication delay. During a backup phase, an Input/Output (I/O) operation selected from a group comprising a create operation and a rename operation is received with one or more local attributes of a local file. The I/O operation is processed to generate one or more remote attributes. The one or more local attributes are stored with the one or more remote attributes. During a reversed phase, a write operation for the remote file is processed, and, the write operation is sent to the primary replication system with the one or more local attributes, where the primary replication system uses a local file handle in the one or more local attributes to access the local file for processing the write operation to sync the local file with the remote file.

Abstract: A system may include processor(s) and a memory in communication with the processor(s) and storing instructions, that when executed by the processor(s), are configured to cause the system to perform a method for cross-region data processing. The system may receive data in a first processing region and may format the data into a plurality of data portions. The system may generate a copy of each data portion and may transmit each data portion copy to a cross-region processor. Responsive to determining the first processing region is functioning, the system may process data portion(s). The system may transmit, to a centralized location, the processed data portion(s). Responsive to determining the first processing region is not functioning, the system may transmit, from the cross-region processor, each data portion copy to a second processing region.

Abstract: A system for analyzing graph databases using intelligent reasoning systems including scalable collection of, and transformation of, graph data into facts suitable for use with programming logic languages doing deductive reasoning. A graph analyzer ingests disparate graph data from across the Internet and transforms the graph data into a fact table. In order to reduce latency and processing congestion, a stream processing engine and sharding strategy are employed to ensure scalability through parallelized processing of programming logic queries. Transformed graph data, now relational data, is utilized with programming logic languages that allow for hypothetical queries whereby an inference engine can deduce new information to satisfy such a query. Furthermore, the self-contained nature of inputs, outputs, and transformations of the system means strict data provenance can be observed and adhered to.

Abstract: In general, various aspects provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for performing data discovery on a target computing system. In various aspects, a third party computing connects, via a public data network, to an edge node of the target computing system and instructs the target computing system to execute jobs to discover target data stored in data repositories in a private data network in the target computing system. In some aspects, the third party computing system may schedule the jobs on the target computing system based on computing resource availability on the target computing system.

Abstract: Computer system compares data across two data sources. Database connectivity drivers access the first and second data sources. RAM receives and stores data from each of the first and second data sources accessed by the drivers. The data from the first data source are stored in a first table in the RAM and data from the second data source are stored in a second table in the RAM. A processor compares data in the first and second tables. The processor is programmed to compare the data by identifying a set of primary keys across the first and second tables. The set of primary keys are a set of one or more columns in the both first and second tables that uniquely identify rows across both the first and second tables.