Abstract: Techniques for change data capture (CDC) log augmentation are described. In some examples, a user configures CDC log augmentation by indicating which data should be included in a CDC log, and the database, when generating a CDC log associated with this configuration, can obtain the associated data and augment the CDC log by inserting this data into it. The augmented data can include one or more fields from a record in a separate database table, where the record can be identified based on the changed record represented by the CDC log.

Abstract: A logical graph is generated using at least a portion of log data received from a set of agents executing on one or more nodes in one or more data centers. The logical graph is augmented using data obtained from one or more agents executing in containerized environments, including by representing communications between pods within the logical graph. The augmented logical graph is used to detect an anomaly.

Abstract: Extract, Transform, Load (ETL) processing may be initiated by detected events. A trigger event may be associated with an ETL process apply one or more transformations to a source data object. The trigger event may be detected for the ETL process and evaluated with respect to one or more execution conditions for the ETL process. If the execution conditions for the ETL process are satisfied, then the ETL process may be executed. At least some of the source data object may be obtained, the one or more transformations of the ETL process may be applied, and one or more transformed data objects may be stored.

Abstract: Systems and methods for generating a machine-learning (ML) model for extracting information from one or more electronic documents, where the ML model can be used as a data object, which can be part of a database command or as part of a document information extraction process that is continuously running (e.g., document information extraction pipeline).

Abstract: A computer-implemented method, computer program product and computing system for: obtaining first system-defined platform information concerning a first security-relevant subsystem within a computing platform; obtaining at least a second system-defined platform information concerning at least a second security-relevant subsystem within the computing platform; combining the first system-defined platform information and the at least a second system-defined platform information to form system-defined consolidated platform information; and generating a security profile based, at least in part, upon the system-defined consolidated platform information.

Abstract: In one embodiment of systems and methods described herein, a computing device is configured to generate and display a user interface including one or more selectable generic options; receive a selection of a data analysis function to perform machine learning; translate the selected function into pre-configured commands for each back-end tool that are specific to each back-end tool for performing the selected function, wherein the pre-configured commands identify and access specific schema with a compatible format for reading the specific schema from each back end tool to expose retail-specific data sets in accordance with the specific schema; execute the preconfigured commands based on the specific schema and retrieve corresponding retail-specific data from a plurality of the back-end tools based on the specific schema; and execute the selected data analysis function on the retrieved retail-specific data from the plurality of back-end tools and generate a data analysis result using Artificial Intelligence-Ena

Abstract: Systems, methods, and non-transitory computer readable media containing instructions allow altering default website display parameters to conform with a neurodevelopmental disorder, epilepsy, visual impairment, and/or cognitive disability profile. In one implementation, a non-transitory computer readable medium contains instructions that cause a processor to alternate default website display parameters to conform with a disability profile by: obtaining an indication that a user of a website has a disability; and based on the obtained indication, implementing a predefined template to alter multiple website default display parameters to conform with needs of the user with the disability; wherein implementing the predefined template impacts presentation of content on a computing device of the user with the disability without impacting presentation of content on other computing devices display to other simultaneous viewers of the website.

Abstract: In an example embodiment, a solution is provided that aggregates records as they are submitted to a third party (on the write path) rather than performing a real-time aggregation when a request is processed that needs the aggregation (read path). More particularly, in an example embodiment, a caching layer is introduced that avoids having to read all usage events to compute an aggregation when a request is received for aggregated data. The caching layer maintains values for various metrics that require aggregation.

Abstract: A building energy management system includes building equipment, a data collector, an analytics service, a timeseries database, and an energy management application. The building equipment monitor and control one or more variables in the building energy management system and provide data samples of the one or more variables. The data collector collects the data samples from the building equipment and generates a data timeseries including a plurality of the data samples. The analytics service performs one or more analytics using the data timeseries and generates a results timeseries including a plurality of result samples indicating results of the analytics. The timeseries database stores the data timeseries and the results timeseries. The energy management application retrieves the data timeseries and the results timeseries from the timeseries database in response to a request for timeseries data associated with the one or more variables.

Abstract: A data management system includes a processor. An estimated ETL level mapping processing unit is operated on the processor to estimate existence of unregistered ETL that is ETL not registered in a repository, to calculate a degree of similarity based on matching between an existing data model and retained data, and to extract a column to be a candidate based on the degree of similarity. The existence of the unregistered ETL is estimated by estimating the presence or absence of connectedness in the ETLs on the basis of correspondence between input data and output data in ETLs by using an execution ETL log relevant to an execution history of the ETL.

Abstract: In some examples, a computing device is able to communicate with a plurality of data clusters. For example, a first data cluster may be configured with a first version of data cluster software including a first library version, and a second data cluster may be configured with a second version of data cluster software including a second library version that is different from the first. The computing device may execute a single instance of an application to send, based at least on information in the first library version, to the first data cluster, a request for first data, and may receive the first data from the first cluster. Further, the computing device may send, based at least on information in the second library version, second data that is based on the first data to the second data cluster to store the second data with the second data cluster.

Abstract: In one embodiment, a device receives, from a requestor, a query function that queries a dataset and an intended use schema associated with the query function. The device determines, using a policy ruleset, whether the intended use schema falls within an available schema for the dataset. The device executes the query function on the dataset to form a result data, when the intended use schema falls within the available schema for the dataset. The device provides the result data to the requestor.

Abstract: Methods and systems for generating multi-operator data transformation pipelines. An example method includes accessing raw data for transformation; receiving a selection of a target table or target visualization, wherein the target table or target visualization is for data other than the raw data; extracting table properties and target constraints; and based on the extracted table properties and target constraints, synthesizing one or more multi-operator data transformation pipelines for transforming the raw data to a generated table or generated visualization.

Abstract: According to one embodiment, an information processing apparatus includes: a processor configured to select a first case based on subject data including at least one feature, and acquire a first prediction value that is a value of an objective variable included in the first case; a first estimator configured to estimate frequency data indicating frequencies of observation values of the objective variable, based on a history of observation values of the objective variable; a second estimator configured to estimate first frequency data indicating frequencies of first prediction values, based on a history of first prediction values acquired before the first prediction value is acquired; and a corrector configured to correct the first prediction value acquired by the processor, based on the frequency data and the first frequency data.

Abstract: A data index establishment method obtains M raw data segments and a first-layer mapping relationship through segment fitting on raw data in a raw data table, and further obtains N first key segments and a second-layer mapping relationship through segment fitting on a first key of each raw data segment. In a subsequent data query process, a multi-layer mapping relationship is input from a to-be-queried key sequentially in descending order, until a location of the to-be-queried key in the raw data table is located.

Abstract: A novel distributed method for machine learning is described, where the algorithm operates on a plurality of data silos, such that the privacy of the data in each silo is maintained. In some embodiments, the attributes of the data and the features themselves are kept private within the data silos. The method includes a distributed learning algorithm whereby a plurality of data spaces are co-populated with artificial, evenly distributed data, and then the data spaces are carved into smaller portions whereupon the number of real and artificial data points are compared. Through an iterative process, clusters having less than evenly distributed real data are discarded. A plurality of final quality control measurements are used to merge clusters that are too similar to be meaningful. These distributed quality control measures are then combined from each of the data silos to derive an overall quality control metric.

Abstract: In accordance with an embodiment, an intelligent load plan that can automatically ensure that a system is in a runnable state and no other conflicting activity can affect the results of the data loads, such as ETLs. Such an intelligent load plan can be used in on data warehousing solutions as well as on a cloud data warehouse solution. The intelligent load plan can, in some embodiments, automatically detect situations based on which it knows it is not supposed to run the load plan.

Abstract: The systems and methods provide continuous integration and continuous deployment pipeline management using pipeline-agnostic rule sets applied to pre-deployment code samples. The system standardizes the application of a rule set to a pre-deployment code sample to use data at a given location, but the system allows for the sample itself to determine which data stream of the data streams at that data location is used. As such, the systems and methods avoid the need for the plethora of rule sets that would overwhelm a user and defeat the purpose of the CaaS product, but the system allows for processing pre-deployment code samples that are specific to the sample.

Abstract: Computing systems, for example, multi-tenant systems create data centers in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives a cloud platform independent declarative specification describing a new datacenter to be created or modifications to an existing datacenter deployed on a cloud platform. The system compiles the cloud platform independent declarative specification to generate a metadata representation of the data center. If the datacenter is existing, the system generates a metadata representation representing modifications to the datacenter to obtain a desired datacenter. The system sends the metadata representation and a set of instructions for execution on a target cloud platform. The target cloud platform executes the instructions to configure the data center. The system provides users with access to the computing resources of the data center configured by the target cloud platform.

Abstract: In various embodiments, a data integration system is disclosed which enables incremental loads into a data warehouse by developing a data partitioning plan and selectively disabling and enabling indexes to facilitate incremental loads into fact tables.

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 operating a communications network that includes at least two users that are communicatively connected to one another via a descriptor-based communication system such as Ethernet. For writing data from a writing user into a user to be written, receive descriptors and data are transmitted from the writing user to the user to be written, in the user to be written, the data being written according to the received receive descriptors, and/or for reading data by a reading user from a user to be read, transmit descriptors are transmitted from the reading user to the user to be read, data being read by the user to be read according to the received transmit descriptors and transmitted to the reading user. A communications network and users are also described.

Abstract: In an example embodiment, machine learning is utilized to automatically present and explain analysis of multidimensional objects categorized based on context in an enterprise data warehouse. The system is capable of handling dependencies to provide clear insights demonstrated in a native language of an end user. The system is multilingual and capable of framing explanations based on natural language processing (NLP), artificial intelligence (AI), and machine learning. It converts the textual predictions into speech synthesis in the user-understandable native format and then dictates the analysis using the speech synthesis.

Abstract: In accordance with an embodiment, described herein are systems and methods for use with an analytic applications environment, for automatic generation of asserts in such environments. A data pipeline or process, such as, for example an extract, transform, load (ETL) process, can operate in accordance with an analytic applications schema adapted to address particular analytics use cases or best practices, to receive data from a customer's (tenant's) enterprise software application or data environment, for loading into a data warehouse instance. Each customer (tenant) can additionally be associated with a customer tenancy and a customer schema. During the process of populating a data warehouse instance, the system can automatically generate dynamic data-driven ETL asserts, including determining a list of columns for tables in the data warehouse; determining a data type for each column; generating an assert for each determined data type; validating the generated assert; and maintaining the generated assert.

Abstract: Provided is a method for improving reliability of artificial intelligence-based object recognition, in which: in a server interworking with an artificial intelligence module, one or more object regions included in learning data including an image of a recognition target object to be recognized through the artificial intelligence module are recognized; object region recognition data which sets the recognized object regions is extracted and is provided to user terminals in a designated order; a procedure for receiving, from the user terminals, object region selection data which selects at least one effective object region corresponding to the recognition target object among object regions included in the object region recognition data is performed; and the object region selection data of respective users received from the user terminals is mutually compared and analyzed by the same object region selection data.

Abstract: The present document relates to an electronic device, a method for providing personal information using same, and a computer-readable recording medium for recording same, wherein the electronic device may include a communication circuit, a storage, a display, and a processor. According to various embodiments, the processor may be configured to generate a smart contract comprising information on categories of personal information to be provided to an external user, information about the external user, and information about a de-identification level of the personal information to be provided; transfer the smart contract to a block chain; receive a request for provision of personal information from the block chain; process personal information of a user on the basis of the smart contract; and transfer the processed personal information to the block chain. Other various embodiments are possible.

Abstract: Concepts for processing a SQL statement comprising a ROLAP sort operation are presented. One such concept comprises: determining whether a ROLAP partitioning column of the SQL statement does not refer to database columns from a sort operation of the SQL statement; and determining whether the ROLAP partitioning columns of the SQL statement are all referenced in the output of the SQL statement. Responsive to determining a ROLAP partitioning column of the SQL statement does not refer to database columns from a sort operation of the SQL statement, and to determining all of the ROLAP partitioning columns of the SQL statement are referenced in the output of the SQL statement, the SQL statement is modified by removing the ROLAP sort operation from the SQL statement.

Abstract: A method for monitoring or controlling equipment of a building includes receiving a first timeseries comprising first data samples of a first variable monitored or controlled by a system and a second timeseries comprising second data samples of a second variable monitored or controlled by the system. The first data samples are at least partially asynchronous with the second data samples. The method includes synchronizing the first timeseries with the second timeseries by aggregating both the first timeseries and the second timeseries using equivalent aggregation intervals. Aggregating the first timeseries generates a third timeseries comprising aggregated values of the first variable and aggregating the second timeseries generates a fourth timeseries comprising aggregated values of the second variable. The method includes performing an automated operation to monitor or control the equipment of the building using the synchronized data samples of the third timeseries and the fourth timeseries.

Abstract: A system, method, and computer-readable medium are disclosed that generate staging data independently from the execution of control scripts, which process the staging data, improving the quality, efficiency, and speed of data processing systems. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers may automatically generate the staging data and validate the staging data and/or output data.

Abstract: System and method of enhancing previously published PDF document files, including files signed or locked to prevent further editing, with enhancement data stored external to the PDF document files. Here an internet server (enhancement server) is configured with a database that stores a plurality of PDF document files, linked with corresponding PDF document URL, enhanced content data, and statistics. When the enhancement server receives a particular PDF document URL request, it returns annotated PDF information that combines the original PDF document and the enhanced content data. This annotated PDF information can be viewed in the GUI of a remote computerized device. The enhancement server can also receive user input from the remote device, store user uploaded data and files, update user statistics, and use this data to enhance the PDF files further. Applications include PDF linked Q&A, lectures, walkthroughs, enhanced media, and chat sessions.

Abstract: A computer-implemented method, a computer program product, and a computer system for minimizing latency in an infrastructure. One or more servers receive a request of deploying a new extract, load, and transform (ELT) logic. One or more servers analyze the new ELT logic to identify source and target locations, analyze logs of existing ELT logics, identify physical locations of infrastructure resources, and identify available physical spaces for moving the infrastructure resources close to each other. One or more servers determine infrastructure resources that need to be moved so that round trip network communication of the new ELT logic are optimized, based on the physical locations of the infrastructure resources, the available physical spaces, and parameters identified through analysis of existing ELT logics. One or more servers move the infrastructure resources that need to be moved.

Abstract: A query processing method includes receiving a query from a requestor. The query is directed to a first data model specifying multiple base data fields. The method includes determining a set of extension bindings for the first data model based on the query. Each binding specifies an extension to the first data model from a set of model extensions and specifies one of the base data fields of the first data model as a node at which the extension is added. The method includes generating a data object from base data values and extension data values according to an extended data model. The extended data model is defined by the first data model extended by, for each binding of the set, adding data fields from the specified extension to the first data model at the specified node. The method includes returning the data object to the requestor.

Abstract: An illustrative computing system generates, based on a plurality of point-of-interest data records each including data representative of a distinct set of features for a distinct point-of-interest associated with a distinct geographic location, a graph data structure that includes the plurality of point-of-interest data records and a plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records. The computing system generates one or more merged point-of-interest data records based on the graph data structure and provides the one or more merged point-of-interest data records to a mapping system to indicate one or more points-of-interest on a user interface map of a geographic area.

Abstract: A computer implemented method includes establishing, by a data intake and query system, a network connection between the data intake and query system and an application and infrastructure monitoring platform. The data intake and query system receives a data stream from the application and infrastructure monitoring platform. The computer implemented method further includes transforming the data stream while receiving the data stream to obtain a transformed data stream. Further, the transformed data stream is analyzed while receiving the data stream to generate analysis results, which are presented.

Abstract: A computer-implemented method, a computer system and a computer program product distribute content in a virtual meeting session. The method includes extracting a plurality of embedded graphics from a presentation. The embedded graphics are selected from a group consisting of web links, images and video data. The method also includes transmitting the plurality of embedded graphics to a participant computing device. Lastly, the method includes displaying a virtual meeting dashboard that includes the plurality of embedded graphics.

Abstract: Embodiments are directed to bandwidth management in distributed file systems. A request stored in a queue may be dequeued. A work credit value may be determined based on a duration since a last job and a work rate associated with the file system such that the work credit value conforms to a maximum threshold value. A job may be initialized based on the dequeued request such that the work credit value may be reduced based on a size of the job. In response to the reduced work credit value being a negative value further actions may be performed, including: determining a time delay based on the reduced work credit value, the work rate, and the size of the job; delaying an execution of the job until the expiry of the time delay such that upon expiry of the time delay, the job is executed to satisfy the request.

Abstract: A webpage containing information to be extracted may undergo changes to a layout of elements that present the information. These changes could result in an inability to retrieve the information later. A first graph is determined that represents elements of a first version of a webpage at a first time. An element in the first graph for which information is being acquired is specified. A relevant portion of the first graph is designated that includes the element and immediate neighbors in the first graph. Later, a second version of the webpage is retrieved, and a second graph of that second version is determined. The relevant portion of the first graph is compared to the second graph. If a match is found, the information of interest is extracted from the specified element of the second graph. This allows extraction of information to proceed even if the layout of elements changes.

Abstract: A system and method for enabling ETL (Extract-Transform-Load) as a service for data processing are disclosed. A user interface (UI) platform includes an input interface layer and an output interface layer. A receiver receives user input, via the input interface layer, of configuration details data corresponding to a desired data to be fetched from one or more data sources. A processor fetches the desired data from said one or more data sources based on the configuration details data to be utilized for the desired data processing scheme; automatically implements a transformation algorithm on the desired data corresponding to the configuration details data and the desired data processing scheme to output a transformed data in a predefined format; and transmits, via the output interface layer, the transformed data to downstream applications or systems in an end-to-end pipeline.

Abstract: The present disclosure involves systems, software, and computer implemented methods for efficient shared bulk loading into optimized storage. One example method includes identifying a data set on a client to load to a server. Load steps that can be performed either on the client or the server are identified. Values for load factors are determined. Load rules are determined that are based on load factors and are for determining processing locations for the load steps. A processing location of either the client or the server is determined for each load step, based on the load rules. Load steps that have a processing location of the client are executed on the data set, on the client. The data set is transferred from the client to the server, over a network. Load steps that have a processing location of the server are executed on the data set, at the server.

Abstract: Presented are concepts for matching a subject to one or more resources or workflow steps. Once such concept comprises obtaining data associated with a subject, the data comprising, for each of a plurality of parameters, a parameter value relating to the subject. A plurality of data groups for characterising the subject is then generated and a classification process is applied to each data group so as to generate a classification result for each data group. The subject is then matched to one or more resources or workflow steps based on the classification results.

Abstract: A method, system, and computer program product for implementing machine learning visual code and action generation is provided. The method includes receiving from a plurality of hardware and software sources, digital description data associated with visual presentations and an action for execution. A resulting code-based class for each portion of the digital description data is generated with respect to the visual presentation. Self learning software code is executed and a type of visual presentation is selected with respect to associated visual features and the code-based class. Additionally, a visual presentation is selected and an action is executed resulting in hardware and software of a server hardware device being operationally modified. The visual presentation is presented to a user.

Abstract: A system may execute a pipelined multiple-tier test stack to support migration of computing resources via a migratory data stream. Via the pipelined multiple-tier test stack, the system may perform extract, transform, and load operations on the migratory data stream. The extract, transform, and load operations may be used to identify applications that may undergo testing. At a generation tier of the pipelined multiple-tier test stack, the system may generate test scripts, which may be used to test the application. The tests may be validated by the system via a validation tier of the pipelined multiple-tier test stack. To govern the operations, the pipelined multiple-tier test stack may rely on a multi-point reference data model.

Abstract: A policy-controlled access system comprising a client device running a local application, a secure tunnel between a client endpoint of the client device, and a mid-link endpoint of a mid-link server to provide network traffic from the client device to the mid-link server. The mid-link server monitors the network traffic, identifies a plurality of policies corresponding to the third-party content, the plurality of policies is based on parental control configuration set by a parent user, stores the plurality of policies corresponding to the third-party content in a local cache on the client device, and receives a request for data from the child user. After the request is made, the local application correlates the third-party content with the plurality of policies stored in the local cache, identifies a policy associated with the request for the data based on correlation, and authorizes the request for the data based on the identified policy.

Abstract: Embodiments relate to learning and determining user interface (UI) compliance with design guidelines. Those guidelines may enforce operability with requirements of an external UI platform. Embodiments receive as an input, a UI comprising a plurality of elements. An image of the UI is rendered, and a plurality of elements of the UI are identified from the image according to a recursive procedure. The plurality of elements are stored in a first logic tree exhibiting a first hierarchical structure having the plurality of elements as leaf nodes. The first logic tree is compared to a second logic tree exhibiting a second hierarchical structure, that is labeled with semantic metadata and stored within a knowledge base of a database. Input for the comparison may comprise the tree and/or additional meta information. Based upon the comparing, an output is generated indicating a similarity between the first logic tree and the second logic tree.

Abstract: Aspects of the disclosure relate to account lineage tracking and automatically executing responsive actions upon detecting an account lineage. A computing platform may receive a first account-change message from a source-level interceptor. The first account-change message may include information identifying a source account associated with a first computing device and identifying a first target account. The first target account may be associated with a target application configured to access the target database. The computing platform may receive a second account-change message from a database-level interceptor. The second account-change message may include information identifying the first target account as a database-level source account and identifying a second target account associated with one or more target databases.

Abstract: A method for execution by at least one processor of a database system includes indexing a first column via a probabilistic indexing scheme. An IO pipeline that includes a probabilistic index-based IO construct for access of the first column is determined based on a query including a query predicate indicating the first column. The probabilistic index-based IO construct is applied in conjunction with execution of the query via the IO pipeline by applying an index element of the probabilistic index-based IO construct to identify a first subset of rows based on index data of the probabilistic indexing scheme for the first column. A filter element of the probabilistic index-based IO construct is applied to identify ones of a first subset of the plurality of column values corresponding to the first subset of rows that compare favorably to the query predicate.

Abstract: Techniques for configuring managed event tables include generating at a first process of an execution node, log data associated with execution of user-defined function (UDF) code. The log data is provided from the first process to a second process of the execution node. The first process is configured as a sub-process of the second process. The log data is formatted using the second process of the execution node, to generate formatted log data. The formatting is based on a configuration of a managed event table that is external to the execution node. The formatted log data is communicated from the second process of the execution node into a managed event table maintained at a computing node that is external to the execution node.

Abstract: An information processing device that detects an anomaly in an in-vehicle network provided in a vehicle includes: a local rule storage in which at least an individual rule which is a rule generated for the vehicle is stored; a global rule storage in which an integrated rule which is a rule generated for a plurality of vehicles including the vehicle is stored; and a processing unit that performs, using a rule stored in at least one of the local rule storage or the global rule storage, an anomaly detection process on a frame transmitted on the in-vehicle network.

Abstract: An apparatus and method for academic search and analytics insights have been provided. The apparatus includes an ingestion component, obtaining data from external heterogeneous sources, to produce ingested data; a processing component for processing the ingested data; a search and analytics component for executing search queries on the ingested data and generating analytics insights on returned search result; and a storage component for storing the ingested data, the storage component acting as a communication data bus for the ingestion component, the processing component and the search and analytics component. Corresponding server and network system are have been provided.

Abstract: Systems and methods are described herein for performing automated audit balance control (ABC) procedures for data that has moved between data stores within an enterprise or other organization. The systems and methods inspect the data at a target data store and determine the quality of the movement of the data to the target data store based on the inspection. For example, the systems and methods can inspect row or record counts for the data in a data store, aggregate numeric sums within the data at the target data store, perform key data value comparisons between different locations that contained the data, perform full data comparisons between different locations that contained the data, perform checksum comparisons, apply complex business rules, and so on, when determining or verifying the completeness and accuracy of data as it arrives to a temporary or permanent location.