Abstract: A system for maintaining consistency of a data value using a probability includes an interface and a processor. The interface is configured to receive a data value for storing. The processor is configured to store the data value in a data element of a data structure and determine, using an adaptive filter, a probability of certainty associated with the data value. The probability of certainty associated with the data value depends on a time since the data value was updated. The adaptive filter provides as output the probability of certainty and store the probability of certainty associated with the data value in the data structure.

Abstract: In one embodiment, techniques are provided for modeling infrastructure from a plurality of modeling perspectives using an intelligent model hierarchy. A repository model for the infrastructure is generated that serves as a root of the intelligent model hierarchy. The repository model includes a root subject and one or more child subjects. One or more information partitions are generated for each subject, each information partition being associated with a respective modeling perspective. One or more child models are associated with each information partition. The one or more child models each containing one or more infrastructure elements that express the modeling perspective of the information partition with which the child model is associated. The repository model and the one or more child models are maintained together in a repository, and infrastructure elements of a selected model may be displayed on demand in a user interface of a client.

Abstract: A method may include receiving a selection of a template defining a manner in which data is stored in one or more database tables operated upon by a software application while the software application performs a function. The selected template may be stored in a first database table. Customizations applied to the selected template are stored in a second database table. In response to the software application performing the function, a virtual customizing table may be generated to include a database view having the selected template from the first database table and the customizations from the second database table. The software application may perform the function based on the virtual customization table, which is not persisted at a database but is generated as needed. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: A peer-to-peer global namespace for storage system metadata federations. Specifically, the disclosure proposes a peer-to-peer metadata federation architecture, where enterprise storage metadata for any and all geo-distributed sites may be distributed across and continually reconciled by a network of nodes, instead of being maintained by a single node assigned to a given geographic location. In implementing a federation, the network of nodes may lack exploitable, centralized points of vulnerability, and therefore, may exhibit no central point of failure. Furthermore, the disclosure proposes the implementation of a global metadata namespace for the enterprise storage metadata spanning the entirety of an enterprise (across all geographic locations). The global metadata namespace may be maintained on each node through event-based synchronization.

Abstract: A system for maintaining consistency of a data value using a probability includes an interface and a processor. The interface is configured to receive a data value for storing. The processor is configured to store the data value in a data element of a data structure and determine, using an adaptive filter, a probability of certainty associated with the data value. The probability of certainty associated with the data value depends on a time since the data value was updated. The adaptive filter provides as output the probability of certainty and store the probability of certainty associated with the data value in the data structure.

Abstract: Disclosed are various embodiments for discovering availability of digital media titles from multiple digital media service providers. A control is presented to establish a relationship between a user account and a first digital media service provider. A first availability for access by the user account of a digital media title is received from the first digital media service provider. A second availability for access by the user account of the digital media title is received from a second digital media service provider. An indication of availability for access of the digital media title by the user account from the first digital media service provider and the second digital media service provider is presented based at least in part on the first availability and the second availability.

Abstract: Disclosed herein are system, method, and device embodiments for implementing semantic discovery. An embodiment operates by retrieving a plurality of entities from a database instance. A semantic graph representation of the plurality of entities is generated within a graphical user interface. Context information is received from a user. A focus node is determined from the plurality of nodes using the context information. A semantic context of the focus node is determined, wherein the semantic context includes the focus node, a subset of the plurality of nodes, and subset of the plurality of edges. Responsive to the receiving, a visual indication of the semantic context is displayed within the graphical user interface.

Abstract: For categorizing encrypted data files, a processor determines a block cipher key length for a data file based on data file contents. The processor encrypts the data file with an encryption cipher using the block cipher key length. The processor further determines a data type for the encrypted data file from macroscopic artifacts of the encrypted data file.

Abstract: Techniques for allowing a user to invoke lifecycle operations on a data store configured in accordance with a data management scheme, without knowledge of the data management scheme. Techniques include receiving user input from a user interface; identifying, in the received user input, an indication of a first lifecycle operation corresponding to a first entry in a template; based on information in the first entry, identifying in the received user input a first configuration value associated with the first lifecycle operation; formatting the first configuration value as at least a portion of at least one argument to a first command; and invoking, via the first command with the at least one argument, a first computer program configured to perform the first lifecycle operation on the data store.

Abstract: Training examples are created from telemetry data, in which each training example engineered features derived from the telemetry data, storage system characteristics about the storage system that processed the workload associated with the telemetry data, and the response time of the storage system while processing the workload. The training examples are provided to an unsupervised learning process which assigns the training examples to clusters. Training examples of each cluster are used to train/test a separate supervised learning process for the cluster, to cause each supervised learning process to learn a regression between independent variables (system characteristics and workload features) and a dependent variable (storage system response time). To determine a response time of a proposed storage system, the proposed workload is used to select one of the clusters, and then the trained learning process for the selected cluster is used to determine the response time of the proposed storage system.

Abstract: A processor may determine that a particular computer-readable vehicle repair order (RO) (e.g., including first and second RO portions) corresponds to an existing cluster of ROs due to the particular RO including RO data that refers to a particular vehicle symptom. The processor may determine that the first RO portion includes first data representative of a non-specific vehicle component and may then responsively also determine that the second RO portion includes second data that the at least one processor can use to determine a specific vehicle component associated with the particular RO. Responsively, the processor may determine the specific vehicle component based on the first and second data and may then add the particular RO to a different cluster of ROs that is arranged to contain ROs that correspond to the particular vehicle symptom and to the specific vehicle component.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model. A method includes: maintaining a plurality of training sessions; assigning, to each worker of one or more workers, a respective training session of the plurality of training sessions; repeatedly performing operations until meeting one or more termination criteria, the operations comprising: receiving an updated training session from a respective worker of the one or more workers, selecting a second training session, selecting, based on comparing the updated training session and the second training session using a fitness evaluation function, either the updated training session or the second training session as a parent training session, generating a child training session from the selected parent training session, and assigning the child training session to an available worker, and selecting a candidate model to be a trained model for the machine learning model.

Abstract: An information management method executed by an information management apparatus that manages a space-time database which uses, as a key, a forward bit string of a bit string converted from space-time data including time data and positional data and which stores, as a value, corresponding data that corresponds to the space-time data, includes converting a range criterion of space-time data being a search object into a bit string, converting, when an index pattern of a first index that corresponds to a forward bit string of a bit string converted and an index pattern of a second index that corresponds to the key stored in the space-time database differ from each other, the first index into a third index of a same index pattern as the index pattern of the second index, and searching for the key using the third index and outputting, as a search result, corresponding data.

Abstract: Systems, methods and apparatus are provided for AI-based generation of data warehouse quality protocols. An attribute classifier may quantify relationships between source data and target data from an enterprise data warehouse. A data quality engine may apply these relationships to identify specific data quality concerns and generate customized data quality metrics.

Abstract: Processor(s) can receive from a first computing device information representing a member, an animal, a location, a wireless device, and a reward. After a second computing device has received a signal from the wireless device, second information can be received. Further, the processor(s) can receive third electronic information. The processor(s) can determine, using at least some of the second electronic information and the third electronic information, that a second computing device is within a respective distance of a third computing device. Moreover, the processor(s) can transmit an alert representing that a user of the second computing device is within a proximity of the animal. The processor(s) can receive an electronic notification that the animal is in custody and provide a portion of the reward to a user of one device and a portion of the reward to a user of another device, based on contributions to the recovery.

Abstract: Protecting sensitive data in snapshots, including: creating a transformed snapshot portion by applying a transformation specified in an access policy to one or more data objects contained within the portion of the stored snapshot, wherein the stored snapshot is a copy of data in a storage system at a particular point in time prior to a request to access the snapshot; and providing access to the transformed snapshot portion.

Abstract: Text input data may be aggregated and mapped to create composite text input data for electronic records. A semantic event may be automatically detected, triggered by a semantic rule and associated semantic tag. The detected semantic event may be flagged, and a text mining result database may be updated by adding an entry to the database. An indication associated with the event may be transmitted, and a back-end application computer server may establish a hierarchy for multiple elements of the electronic records. The computer server may determine a weight variable and response variable for each element in the hierarchy and apply a hierarchical credibility weighting methodology to the elements from level 1, representing the least granular level in the hierarchy, to level n, representing the most granular level in the hierarchy, calculated recursively from level n, to determine a final estimated credibility for the electronic records.

Abstract: In some implementations, a monitoring device may receive configuration information associated with an extract, transform, load (ETL) pipeline that includes one or more data sources and one or more data sinks. The monitoring device may generate, based on the configuration information, lineage data related to a data flow from the one or more data sources to the one or more data sinks in the ETL pipeline. The monitoring device may generate one or more predicted quality metrics associated with the ETL pipeline using a machine learning model. The monitoring device may generate a visualization in which multiple nodes are arranged to indicate the data flow from the one or more data sources to the one or more data sinks and further in which the one or more predicted quality metrics are encoded within the visualization.

Abstract: A method for performing a backup includes: making a first determination that a last backup of assets is paused; obtaining, based on the first determination, a completed asset list and a non-completed asset list for the last backup; initiating a new backup for assets on the completed asset list for the last backup; and resuming backing up of assets on the non-completed asset list for the last backup.

Abstract: Computer systems and associated methods are disclosed to implement a database dependency monitoring system (DDMS) that periodically collects activity data from an inventory of databases and generates dependency graphs indicating data dependencies among the databases. In embodiments, the collection of the activity data may be implemented as three sets of jobs that are run periodically. In the first job set, the databases are checked to see if they can be connected to. In the second job set, queries are run in each of the available databases to generate output files containing their activity data. In a third job set, the output files are transformed and loaded into a metadata store, which can be used to generate the dependency graph based on the collected activity data. Advantageously, the disclosed system may be used to adaptively monitor a changing inventory of many databases, while causing little or no performance impact on the databases.