A central computer system receives a first plurality of event records, each event record identifying one or more events that have occurred in a device of a plurality of different devices. The central computer system identifies, from the first plurality of event records, a first group of event records that identify a same first set of one or more events that occurred on a first subset of the devices. The central computer system determines that a total number of the event records in the first group of event records exceeds a first threshold criterion. In response to determining that the total number of the event records in the first group of event records exceeds the first threshold criterion, the central computer system sends to a destination, information about the first set of one or more events.

In some examples, migration context and flow graph based migration control may include ascertaining an application that is to be migrated from a physical environment to a cloud environment, and determining a migration issue associated with the migration of the application. Migration context and flow graph based migration control may further include identifying, from a historical issue database, a plurality of historical issues, determining, for the migration issue and the plurality of historical issues, unified proximities, sorting, based on the determined unified proximities, the historical issues, selecting, from the sorted historical issues, a topmost historical issue, and determining, from the topmost historical issue, a resolution associated with the topmost historical issue. Further, migration context and flow graph based migration control may include executing the resolution to resolve the migration issue, and performing, based on the resolved migration issue, migration of the application from the physical environment to the cloud environment.

A query term analytics system receives a search query from a user device. The system has an engine enhanced with the ability to track query terms using in-memory counters and leveraging an inverted index of content stored in a content repository. The search query is run on the content and, contemporaneously the engine performs a query term analysis on the query terms to produce query term analytics. The query term analysis includes an impact analysis that determines an impact of removing a keyword or keyword criteria from the search query. A compressed bitset can be used to indicate whether a keyword is in the content. The engine can accumulate statistics using the in-memory counters while the search query is being processed. Using the statistics thus accumulated, a query term analytics report is generated and provided to the user device for presentation on the user device.

Automatically generating an explanation for a decision prediction from a machine learning algorithm includes using a first processor of a computing device to run the machine learning algorithm using one or more input data; generating a decision prediction output based on the one or more input data; using a second processor to access the decision prediction output of the first processor; generating additional information that identifies one or more causal relationships between the prediction of the first algorithm and the one or more input data; and providing the additional information as the explanation in a user-understandable format on a display of the computing device.

Systems, devices, and methods are discussed that provide for developing custom reports.

Systems and methods are disclosed for processing and executing queries against one or more dataset. As part of processing the query, the system determines whether the query is susceptible to a significantly imbalanced partition. In the event, the query is susceptible to an imbalanced partition, the system monitors the query and determines whether to perform a multi-partitioning determination to avoid a significantly imbalanced partition.

A method begins by a dispersed storage (DS) processing module collecting an event record, a record regarding processing of an event request, and a plurality of records regarding processing of a plurality of sub-event requests to produce a collection of records. The event record includes information regarding an event, wherein the event is a user access operation or a system administrative operation initiated by a device affiliated with the DSN. The record regarding processing of the event request includes information regarding a dispersed storage (DS) processing module of the DSN processing the event request to produce the plurality of sub-event requests. The plurality of records regarding processing of the plurality of sub-event requests includes information regarding a plurality of DS units of the DSN processing the plurality of sub-event requests. The method continues with the DS processing module evaluating the collection of records to produce performance information regarding the DSN.

Systems and methods for generating a fingerprint including multiple tracking identifiers. Control circuitry receives a first tracking identifier from a first component of a network. The first tracking identifier is associated with a data request sent to the first component. The control circuitry identifies parameters based on a configuration of the first component. The control circuitry transmits an application programming interface (API) request for information related to the parameters from the first component. The control circuitry receives information related to the parameters for the first component in response to the API request. The control circuitry determines a second tracking identifier based on the first tracking identifier and the information related to the parameters for the first component. The control circuitry transmits the second tracking identifier to the first component. The first tracking identifier and the second tracking identifier are combined to generate a fingerprint in connection with the data request.

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. The processor then compares the data in the first and second tables, which comparison can include: determining, based on the identified set of primary keys, a total number of mismatched cell values across the first and second tables; and computing a score for the comparison of the first and second tables, where the score is computed based on the total number of mismatched cell values. The computer system can then generate an electronic comparison report based on the comparing of the first table and second table.

An integrated circuit comprises a set of processor cores, wherein each processor core of the set of processor cores includes BIST logic circuitry and multiple memory blocks coupled to the BIST logic circuitry. Each processor core further includes multiple power control circuitry, where each power control circuitry of the multiple power control circuitry is coupled to a respective processor core of the set of processor cores, multiple isolation circuitry, where each isolation circuitry of the multiple isolation circuitry is coupled to a respective processor core of the set of processor cores, a built-in-self repair (BISR) controller coupled to the each of the set of processor cores, each of the multiple power control circuitry, and each of the multiple isolation circuitry, and a safety controller coupled to the BISR controller, the multiple power control circuitry, and to the multiple isolation circuitry.