Abstract: A system including first computer memory storing a full data set representable in rows and columns, a second computer memory storing executable instructions, and processors configured to execute the instructions to cause presentation of data of the full data set on a display including columns of data each having data fields, receive user input identifying a column of the data set, determine items to modify in information in the data fields of the identified column, generate and cause display of an indication of a proposed change action to modify the determined items, and in response to a user input indicating a selection of the indication of the proposed change action, update the presentation of the data based on the change action to modify information displayed in the data fields of the identified column of the data, and store a log of the change action.

Abstract: In various example embodiments, a comparative modeling system is configured to receive selections of a data set, a transform scheme, and one or more machine-learning algorithms. In response to a selection of the one or more machine-learning algorithms, the comparative modeling system determines parameters within the one or more machine-learning algorithms. The comparative modeling system generates a plurality of models for the one or more machine-learning algorithms, determines comparison metric values for the plurality of models, and causes presentation of the comparison metric values for the plurality of models.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computer network security risk assessment. One of the methods includes obtaining compromise likelihoods for user accounts. Information describing a network topology of a network is obtained, with the network topology being nodes each connected by an edge to other nodes, each node being associated with a compromise likelihood, and one or more nodes are high value nodes associated with a compromise value. Unique paths to each of the high value nodes are determined for a particular user account. An expected value for each path is determined based on the compromise likelihood of the particular user account, the compromise likelihood of each node included in the path, the communication weight of each edge included in the path, and the compromise value associated with the high value node. User interface data is generated describing at least one path.

Abstract: A datacenter has more computing power than a personal computer. The personal computer sends a request to perform an operation on a data set to the datacenter. The datacenter evaluates various inputs to determine if, despite the datacenter's computing power, the personal computer is likely to complete the operation faster. Based on the determination, the datacenter may perform the operation, send the data set to the personal computer for the personal computer to process, or start a competitive computation. As a result, a user interface can be more responsive. Machine learning processes can be used to improve predictions.

Abstract: Systems, computer program products, and computer-implemented methods for generating interactive graphical user interfaces, software-based workflows, and data integrations using catalogs of workflow applications and auto-generation of aspects of the workflows.

Abstract: Systems and methods are provided for investigation network activities. Network activity information may be accessed. The network activity information may describe for an individual (1) respective relationship with one or more persons; and (2) respective activity status information indicating whether a given person has engaged in a particular activity. A network activity graph may be generated based on the network activity information. The network activity graph may include two or more nodes representing the individual and the one or more persons. Connections between the nodes may represent the respective relationships between the individual and the one or more persons. Data corresponding to the network activity graph may be presented through an interface.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for automating the transfer/syncing of datasets or other artifacts from one security domain (e.g., a low security side environment) to another security domain (e.g., a high security side environment) in a seamless manner that complies with requirements of a data transfer mechanism used to transfer data between the two security domains while ensuring data integrity and consistency between the two security domains.

Abstract: A computer-implemented method of integrating decoupled front-end and back-end processes is disclosed. The method comprises receiving a front-end configuration including validation specifications and a back-end configuration including data validation rules; receiving a data item via forms-based interface associated with the front-end configuration, the data item having been validated based on the validation specifications; mapping the data item to a back-end data object; detecting a conflict between the validation specifications and the validation rules; altering a back-end validation process associated with the back-end data object; causing storing the data item in a database system in association with the back-end data object.

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: Aspects of the present disclosure relate to performing agnostic data integrity checks on source data, and based on the data integrity checks, generating a human-readable report that may be useable to identify specific errors or anomalies within the source data. Example embodiments involve systems and methods for performing the data integrity checks and generating the human-readable reports. For example, the method may include operations to ingest data from a source database through a data pipeline and into a local database, access the data from the data pipeline, determine a data type of the data, determine subtypes of data elements which make up the data, determine a count of each subtype, and generate a human-readable report, to be displayed at a client device.

Abstract: Systems and methods for isolating applications associated with multiple tenants within a computing platform receive a request from a client associated with a tenant for running an application on a computing platform. Hosts connected to the platform are associated with a network address and configured to run applications associated with multiple tenants. A host is identified based at least in part on the request. One or more broadcast domain(s) including the identified hosts are generated. The broadcast domains are isolated in the network at a data link layer. A unique tenant identification number corresponding to the tenant is assigned to the broadcast domains. In response to launching the application on the host: the unique tenant identification number is assigned to the launched application and is added to the network address of the host; and the network address of the host is sent to the client associated with the tenant.

Abstract: A method is provided for output validation of data processing systems, performed by one or more processors. The method comprises performing a data comparison between a first data table and a second data table to determine a data differentiating table, wherein the first data table is based on an output of a first data pipeline, and wherein the second data table is based on an output of a second data pipeline; performing a schema comparison between the first data table and the second data table to determine a schema differentiating table; generating a first output validation score based on the data differentiating table; generating a second output validation score based on the schema differentiating table; and generating a summary comprising both the first and second output validation scores.

Abstract: An interactive user interface for receiving and displaying data is described. The interactive user interface may display data sets from a plurality of external applications and/or data sources. Received data sets may be compiled to form an interactive graphical unit, also called a “card,” that may be displayed in a format based upon that of the native external application of the received data sets. Cards may be grouped with other cards. A card may include a link which allows users to access the native external application of the card to make any desired modifications or changes.

Abstract: Example embodiments involve a metrics collection system for collecting software usage metrics from one or more client devices at deployments. A computer, such as a server configured to execute the metrics collection system, collects software usage metrics (e.g., as a metrics submission from a client device) of the software product at the deployment, identifies a metrics type of the software usage metrics collected, assigns the software usage metrics to a metrics category, and calculates and updates a metrics score of the metrics category, based on the software usage metrics collected.

Abstract: A method, performed by one or more processors, including: receiving a user query; deriving, based on the user query, a search engine query for use with search engine software and a data access query for use with data access software; sending, to the search engine software, the search engine query to cause the search engine software to locate first data stored in a search engine index; sending, to the data access software, the data access query to cause the data access software to locate second data stored in a distributed data store; receiving, from the search engine software, the first data; and receiving, from the data access software, the second data.

Abstract: Example embodiments relate to a system to generate and cause display of a specially configured graphical user interface to receive and present collections of images. According to certain example embodiments, an image analysis system: receives an image file from a client device; generates a hash value based on the image file; performs a comparison of the hash value with a list that comprises a collection of hash values; identifies a match to the hash value among the collection of hash values; assigns a label to the image file in response to identifying the match among the collection of image files from the list; and indexes the image file at a memory location identified by the label assigned to the image file.

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, automatically tag and group those clustered data structures, and provide results of the automated analysis and grouping 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, rules, indicators, or scenarios so as to generate scores, reports, alerts, or conclusions that the analyst may quickly and efficiently use to evaluate the groups of data clusters.

Abstract: Systems and methods are provided for implementing a machine learning approach to modeling entity behavior. Fixed information and periodically updated information may be utilized to predict the behavior of an entity. By incorporating periodically updated information, the system is able to maintain an up-to-date prediction of each entity's behavior, while also accounting for entity action with respect to ongoing obligations. The system may generate behavior scores for the set of entities. In some embodiments, the behavior scores that are generated may indicate the transactional risk associated with each entity. Using the behavior scores generated, a user may be able to assess the credit riskiness of individual entities and instruct one or more individuals assigned to the entities to take one or more actions based on the credit riskiness of the individual entities.

Abstract: Example embodiments relate to a network-based workflow system, employed for receiving workflows, defining one or more data-object types based on the workflows, generating data-objects, assigning a workflow from among the one or more workflows to the data-object, and managing the data-object through various states of based on the workflow. As discussed, a “workflow” refers to orchestrated and repeatable patterns enabled by a systematic organization of resources into processes that transform and modify presentations of data-objects based on corresponding data-object states. A workflow may therefore comprise a set of states, wherein each state is linked to another state by one or more transitions, and wherein the transitions are associated with a set of events which may occur at each state.

Abstract: A system and method for authenticating users of a data processing platform stores a mapping of a unique user platform identifier to multiple user identity provider identifiers associated with multiple realms for a same user. In some examples, the method includes receiving a request from a client device to establish an access session to perform one or more actions on data of the data processing platform and receiving, from at least one of the first external identity provider of the first realm or the second external identity provider of the second realm, a user identity provider identifier associated with the request. In certain examples, the method includes granting permission to perform the one or more actions on the data of the data processing platform based at least in part on the received user identity provider identifier.