Abstract: Systems and methods provide real-time processing in edge servers of a network. In one example, an edge server receives real-time streaming data from at least a first client device and processes, in real-time, the received real-time streaming data to produce real-time edge processed data. The edge server receives a request for real-time streaming data from at least a second client device and provides in real-time, the real-time edge processed data to the requesting second client device. In some embodiments the edge server forwards the received real-time streaming data, and if desired, the edge processed data to a central server or other server, for processing.

Abstract: A data pipeline including a plurality of graph pipeline paths is obtained. Each of the graph pipeline paths may include pipeline nodes, at least one of the pipeline node may have at least two inputs. Each of the inputs may comprise outputs of two or more other pipeline nodes. A linear pipeline path interface is provided for creating and presenting a linear pipeline path of the data pipeline. The linear pipeline path may include pipeline nodes, each being limited to a single input and a single output. The linear pipeline path interface may be limited to interacting with linear pipeline paths. A graph pipeline interface is provided for presenting and modifying the data pipeline. The linear pipeline path interface may be switched to the graph pipeline interface in response to a first user input.

Abstract: Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.

Abstract: Systems and techniques for accelerating relationship visualizations from data objects are described herein. The configuration and/or display of a relationship matrix may be automatically determined from the data objects. The relationship matrix may display relationships through gradient, hue, color, and/or saturation. The relationship matrix may be navigable and/or interactive to accelerate relationship visualizations.

Abstract: Systems and methods for simplified frontend processing and visualization of large datasets are provided. In example embodiments, a plurality of data objects are accessed. One or more of data objects from among the plurality of data objects are grouped into a first group. A group identifier that identifies data objects included in the first group is created. A visualization comprising a first node that represents the first group is generated. The first node is linked to the group identifier. The visualization is presented on a user interface of the user device. User input indication a user-specified action and the group identifier is received. The user-specified action is performed with the data objects identified by the group identifier.

Abstract: Example embodiments relate to a network-based vulnerability detection system configured to access a database of customer transaction data corresponding to a set of card readers that includes transaction codes, receive an identification of a set of compromised card readers among the set of card readers, identify common transaction codes within the transaction data of the set of compromised card readers, and correlate the common transaction codes to one or more instances of fraud associated with the compromised set of card readers. In some example embodiments, the vulnerability detection system may be applied to monitor one or more card readers, receive transaction data corresponding to transaction conducted through the card readers, identify the common transaction codes correlated to the instances of fraud, and cause display of a notification that includes an indication of the instance of fraud at a client device.

Abstract: Systems, methods, and non-transitory computer readable media are provided for presenting a user interface for fault analysis. Fault information may be accessed. The fault information may identify faults for one or more machines. A fault analysis interface may be provided. The fault analysis interface may include an organization view, an instance view, a subsystem view, or a map view. The fault analysis interface may enable presentation of the organization view, the instance view, the subsystem view, and the map view. The fault analysis interface may display correlations of the faults using visuals and spatial locations of the visuals.

Abstract: Various systems and methods are provided for accessing and traversing one or more data structures and generating a functional user interface that can enable non-technical users to quickly and dynamically search for resources of an organization and/or associated documents, events, entities, and/or other data. The user interfaces are interactive such that a user may make selections, provide inputs, and/or manipulate outputs. In response to various user inputs, the system automatically accesses and traverses data structures relating to resources, documents, events, entities, and other data, identifies resources, documents, events, entities, and/or other data that meet search criteria, and returns search results including resources that meet the search criteria and/or resources that are associated with documents, events, entities, and/or other data that meet the search criteria.

Abstract: In an embodiment, a data processing method comprises creating and storing a plurality of analytical notebooks in digital computer storage, wherein each of the analytical notebooks comprises notebook metadata that specifies a kernel for execution, and one or more computational cells, wherein each of the cells comprises cell metadata, a source code reference and an output reference; receiving, in association with a first cell among the one or more cells, first input specifying computer program source code of a function, wherein the function defines an input dataset, a transformation, and one or more variables associated with output data; storing the first cell, excluding the output data, using a first digital data storage system and updating the source code reference to identify the first data storage system; using the kernel specified in the notebook metadata, executing an executable version of the source code to result in generating the output data; storing the output data using a second digital data storage

Abstract: Errors encountered by executing applications can be recorded in one or more logs. A search engine can be configured to retrieve error data from the one or more logs using pre-specified rules. A portion of the error data can be included in a small portable message (e.g., SMS text message) and sent to the developers or administrators of the applications. An administrative console can generate different visualizations based upon what errors the search engine retrieved.

Abstract: In various example embodiments, a system and method for transforming instructions for collaborative updates are described herein. A group of instructions for an update of an element depicted in a client device version of a user interface are generated. The group of instructions is executed and the group or a subset of instructions are transmitted to a server. The server accepts or rejects the instructions. The server may execute the instructions to update a server version of the element. The server sends accepted instructions to the other or all client devices.

Abstract: An interactive data object map system is disclosed in which large amounts of geographical, geospatial, and other types of data, geodata, objects, features, and/or metadata are efficiently presented to a user on a map interface. The interactive data object map system allows for rapid and deep analysis of various objects, features, and/or metadata by the user. A layer ontology may be displayed to the user. In various embodiments, when the user rolls a selection cursor over an object/feature an outline of the object/feature is displayed. Selection of an object/feature may cause display of metadata associated with that object/feature. The interactive data object map system may automatically generate feature/object lists and/or histograms based on selections made by the user. The user may perform geosearches, generate heatmaps, and/or perform keyword searches, among other actions.

Abstract: Systems, methods, and non-transitory computer readable media may provide workflow assistance for performing operations on information. Information defining a graph may be accessed and a set of operations for the graph may be provided. The graph may represent objects with nodes and connections among the objects with edges. A user's selection of one or more operations from the set of operations may be received. A workflow of operations for the graph may be generated based on the user's selection. The workflow of operations may include the operation(s) selected by the user.

Abstract: Techniques for implementing a streaming transaction in a transaction based data storage system is disclosed. In an embodiment, a server computer system stores a dataset comprising a plurality of files where the dataset comprises a corresponding version number. The server computer system receives a command to modify the dataset and, in response, starts a streaming transaction for the dataset. During the streaming transaction, the server computer system receives a plurality of updates to the dataset, wherein each of the plurality of updates modifies one or more files of the plurality of files. The server computer system executes the plurality of updates in the dataset without modifying the corresponding version number of the dataset. When the server computer system commits the streaming transaction to the dataset, the server computer system increments the corresponding version number of the dataset.

Abstract: Systems and methods are provided for facilitating the transformation of data from a tabular data set organized according to a data schema to an object based data set organized according to a data ontology. The provided systems and methods offer a graphical user interface for mapping the tabular based data to the object based data set according to the data ontology. The tabular based data may be transformed according to the mapping.

Abstract: Systems and methods are provided for providing continuous configuration deployment. A configuration definition object may be obtained from a remote datastore. The obtained configuration definition object may be stored in a local datastore. The configuration definition object may be obtained and stored in advance of a scheduled maintenance. The configuration definition object may be obtained in response to the configuration definition object being committed to the remote datastore. The configuration definition object may be used to generate different configuration objects. A configuration object may be generated from the configuration definition object and one or more system characteristics. A service request may be received, and the configuration object may be executed to perform a configuration of a computing system.

Abstract: Systems and methods are provided for analyzing and visualizing relationship of multi-layered datasets. A system stores original datasets in a datastore. The system generates first derivative datasets from the original datasets, and generates second derivative datasets from at least the first derivative datasets. The system determines relationships among the original datasets, the first derivative datasets, and the second derivative datasets, based on an analytical relationship between two datasets, a similarity relationship between two datasets, a modification relationship between two datasets, and a user-interaction relationship between two datasets. Then, the system generates a node map including at least part of the original datasets, the first derivative datasets, and the second derivative datasets as a node, and at least part of the determined analytical, similarity, modification, and user-interaction relationships between two nodes as a link.

Abstract: A method of incrementally replicating investigative analysis data is disclosed along with a system for performing the same. The method and system provide the ability to break a data replication job into multiple “replication chunks” which can be exported and imported separately. By doing so, the method and system can efficiently replicate large numbers of data object changes over an unreliable data network.

Abstract: Methods, systems, and computer-readable media described herein may include: obtaining first data from a first datastore managed by a first entity, the first data comprising a first status of a first task of a first subsidiary workflow that is part of an integrated workflow; integrating the first data into a second datastore managed by a second entity that manages the integrated workflow, with an integration layer; generating a graphical user interface to present an interactive graphical object that displays the integrated first data and the integrated workflow to a user; receiving one or more updates from the user to the integrated first data, where the one or more updates are based on one or more graphical user interactions with the integrated first data; identifying a change to a portion of the first data; and writing the change in the first datastore using the integration layer interface.

Abstract: Systems and methods scale an instance group of a computing platform by determining whether to scale up or down the instance group by using historical data from prior jobs wherein the historical data includes one or more of: a data set size used in a prior related job and a code version for a prior related job. The systems and methods also scale the instance group up or down based on the determination. In some examples, systems and methods scale an instance group of a computing platform by determining whether to scale up or down the instance group by at least evaluating on-demand job request data for resource units (RUs), observing current job state data, and predicting resource unit need using historical data from prior related job executions. The systems and methods scale the instance group up or down based on the determination.