Abstract: Example embodiments described herein pertain to a geographic information system (GIS), configured to obtain geospatial data representing a geographic area, assign a projection and coordinate system to the geospatial data, apply a transformation to the geospatial data, and generate a tile cache based on the transformed geospatial data, the tile cache including the determined projection and coordinate system.

Abstract: Embodiments of the present disclosure relate to a data analysis system for grouping and enriching data items for presentation to an analyst through a user interface. Data items from one or more data sources are combined into memory-efficient clustered data structures, which may be stored as one or more data tables in a database. Analysis and scoring of those clustered data structures can be performed by utilizing various criteria or rules to generate scores, reports, alerts, or conclusions that may aid an analyst in evaluating the clustered data structures. The analysis and scoring may also be added to the clustered data structures which are stored as one or more data tables in a database. The analyst may be prompted to create a dossier format or specification and to additional enrichments to be performed on the raw data items in the clustered data structures. The system may then search, group, or filter the raw data items based on the analyst-defined dossier format, as well as add enrichments to the data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a feature clustering of users, user correlation database access, and user interface generation system. The system can obtain information stored in different databases located across geographic regions, and determine unique users from the different information. The information can be included in unique records in the databases, with each record describing a particular user, and with each user described with imperfect identifying information. The system can analyze the different information utilizing machine learning models, and can associate each record with a particular unique user. The system can obtain identifications of items associated with each user, and determine the propensity of the user to disassociate with one or more items, or determine likelihoods of future association with different items not presently associated with the user.

Abstract: A user data visualization and parsing system may receive from a user a selection of a first data item from a data set, the data item associated with a location identifier. The data visualization and parsing system may extract a first value of the first data item associated with the location identifier and identify, in a second data set of the data stream, a second data item associated with the location identifier. The system may extract a second value of the second data item associated with the location identifier, generate a visual representation of the first and second values, and display the visual representation to the user through the user interface.

Abstract: Disclosed are data gathering and analysis systems, methods, and computer-readable storage media to facilitate an investigation process. The method includes accessing a data object representing an investigative issue as part of initiating an investigative session. The method further includes causing presentation, on a display of a device, of a user interface configured to receive user search queries and present search results for each received search query. The method further includes tracking user activity including one or more user actions performed during the investigative session. The method further includes creating a record of the user activity, and linking the record of the user activity with the data object representing the investigative issue.

Abstract: Systems, methods, and non-transitory computer-readable media can obtain data form one or more data sources. The data from the one or more data sources can be processed into one or more data records. Each data record can include at least an identification, a data type, and data to be stored. The data records can be organized into a tree data structure. The tree data structure can be stored as an intermediate data layer in a data analysis platform.

Abstract: Systems, methods, and non-transitory computer readable media are provided for managing expiration of modules. An expiry dataset may be maintained. The expiry dataset may include a set of identifiers corresponding to a set of modules, a set of expiry values for the set of modules, and a set of termination tasks for the set of modules. A request to refresh a module may be received from a client. Responsive to the reception of the request, an expiry value and a termination task for the module within the expiry dataset may be updated. The expiry value may be independent of a timestamp associated with the request.

Abstract: Systems and methods are disclosed herein for reducing a risk of associating with a client that may engage in illegal activity. A system accesses data associated with an entity for a given context, applies a plurality of AI models to the data based on the context to generate a plurality of AI assessments. Data for showing risk factors, assessments of the risk factors, and data for evaluating risk factors can be transmitted for rendering in a user interface in a display device. Analyst feedback can be received and used to update the AI models.

Abstract: Systems and methods for dynamically generating application programming interfaces and managing functions associated with a data object type. In an aspect, the system accesses an object definition for a type of data object. The system generates an application programming interface associated with the type of data object, based at least partly on the object definition. The system determines a change to the object definition for the type of data object and updates the application programming interface based at least partly on the change to the object definition.

Abstract: Systems and methods are provided for collaborating with different object models. Data corresponding to one or more source objects is received. The source objects is stored in a first object model, and each of the source objects is associated with information describing an entity. Matches between the respective information associated with the one or more source objects and respective information associated with one or more target objects are determined based on a query. The target objects are stored in a second object model. The one or more source objects are ranked based at least in part on the matches. A list of the ranked source objects are provided through an interface, the interface indicating a number of matching target objects for each of the source objects.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage media for a data record resolution and correlation system. One of the methods includes obtaining data sets each including records associated with entities, the records each specifying information for a plurality of aspects of an entity, the information being encoded in the records, for each of the data sets, according to a respective format. One or more bundles are determined from the data sets, with each bundle indicating records determined to be associated with a same entity and determined using similarity rules that compare aspects specified in the records. Information describing a particular bundle is presented to a reviewing user, and the reviewing user can specify one or more records included in the particular bundle that are properly matched. The particular bundle can be updated based on the reviewing user's specification.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for data analysis. A user interface comprising boards corresponding to one or more objects and one or more operations on the input and/or output objects of the boards can be generated for high-scale top-down data analysis.

Abstract: A user interface for working through workflows can include a dual-region approach. The first display region can display a series of workflows that an assigned worker (“assignee”) may have. Each of the workflows can have one or more tasks associated therewith. Each workflow and/or task can be associated with one or more triggers that initiate the assignment of that workflow and/or task. In response to selection of a workflow or task, the second display region can display information associated with the workflow or task.

Abstract: Systems and methods are provided for sharing maps in a collaborative environment using classification-based access control. The generation of and dissemination of maps and/or data within such maps can be governed by classification-based access control, where a user's classification level can determine whether or not maps and/or data within those maps can be seen. In scenarios whether a plurality of users wishes to collaborate on the same map, the systems and methods provided herein generate multiple versions or views of the same map in accordance with different classification levels. In this way, users with different classification levels can nevertheless see the same map and engage in collaborations regarding the same map, while maintaining control of sensitive data.

Abstract: A computer-implemented system and method for data revision control in a large-scale data analytic systems. In one embodiment, for example, a computer-implemented method comprises the operations of storing a first version of a dataset that is derived by executing a first version of driver program associated with the dataset; and storing a first build catalog entry comprising an identifier of the first version of the dataset and comprising an identifier of the first version of the driver program.

Abstract: Systems and techniques for indexing and/or querying a database are described herein. Multiple, large disparate data sources may be processed to cleanse and/or combine item data and/or item metadata. Further, attributes may be extracted from the item data sources. The interactive user interfaces allow a user to select one or more attributes and/or other parameters to present visualizations based on the processed data.

Abstract: A system of one or more computing devices is utilized for, among other purposes, creating a template-driven search interface and conducting searches thereon. In an embodiment, the system comprises: a template repository; search templates in the template repository, the search templates comprising at least: field specification data that specify search interface fields for obtaining search input data, and query specification data that specify how to generate structured queries based on the search input data obtained for the one or more of the search interface fields; a search field generator that generates search fields indicated by the field specification data; a template loading module, coupled to the template repository, that identifies available search templates in the template repository; and a search interface generator, coupled to the search field generator and template loading module, that generates different search interfaces depending on which template is selected.

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 or rules so as to generate a tiled display of the groups of related data clusters such that the analyst may quickly and efficiently evaluate the groups of data clusters. In particular, the groups of data clusters may be dynamically re-grouped and/or filtered in an interactive user interface so as to enable an analyst to quickly navigate among information associated with various groups of data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation.