A method may include presenting a user interface on a display device of a computing device, the user interface including: a search query input element; a plurality of graph type options; a graph level selection element; and a graph presentation area; receiving a search query inputted into the search query input element, the search query identifying a concept object in an ontology; retrieving data associated with the concept object from a graph database based on selections made in the graph type options and the graph level selection element, the data including a set of result objects related to the concept object; and rendering a hierarchical graph in the graph presentation area, the hierarchical graph illustrating the set of result objects and the concept object as interactive nodes.

Embodiments provide methods and systems for merchant data cleansing in payment network. Method performed by server system includes accessing electronic payment transaction records from transaction database. Each electronic payment transaction record includes merchant data fields. Method includes determining set of electronic payment transaction records with ambiguous merchant data fields having matching probability scores less than predetermined threshold value computed by probabilistic matching model and identifying at least one issue for non-matching of each of set of electronic payment transaction records. Method includes determining data model based on at least one issue of each of set of electronic payment transaction records. Data model is one of: phone-to-city model, payment aggregator model, and merchant name normalization model. Method includes updating set of electronic payment transaction records with unambiguous merchant data fields corresponding to ambiguous merchant data fields by applying data model to each of set of electronic payment transaction records.

Embodiments of the present disclosure relate to sharing database roles using hidden roles. A database role may be generated within a database container having a plurality of data objects, wherein the database role exists exclusively within the database container. A set of grants to a particular subset of the plurality of data objects of the database container may be assigned to the database role. For each of a set of share objects to which the database role is to be granted: a hidden role having no identifier may be created, the database role may be granted to the hidden role, and the hidden role may be granted to a share object. Each of the set of share objects are mounted within a consumer account to generate a set of imported database containers within the consumer account, wherein each imported database container includes an individualized grant of the database roles.

A back-end application computer server may access a potential metadata entries data store containing a set of potential metadata entries, each entry including at least a data element name and a data element definition. A metadata collection system may be executed to automatically populate a metadata template based on the set of potential metadata entries. The system may update entries in the metadata template using a translation tool and validate the updated entries in the metadata template to ensure that required data elements are present. The system may also certify the validated entries load the set of certified metadata entries, including the certified data element names and certified data element definitions, into an enterprise metadata repository data store. Electronic messages may be exchanged to support at least one interactive user interface display associated with certification of the metadata template.

A DBMS receives a database-access request that includes an instruction to non-destructively read a database table row. The DBMS assigns the request a TSN identifier and creates a TSN image that identifies all TSNs assigned to transactions that are not yet committed. The DBMS traverses a linked list of log entries that identifies a chronological history of transactions performed on the same row. The DBMS infers that the table row currently contains data stored by the most recently logged transaction that is not contained in the TSN image and that has thus been committed. The DBMS then continues to process statements of the transaction based on the assumption that the row contains the inferred value. The DBMS performs this procedure without acquiring a shared lock on the data page or on the index leaf page that points to the table row.

A DBMS receives a database-access request that includes an instruction to non-destructively read a database table row. The DBMS assigns the request a TSN identifier and creates a TSN image that identifies all TSNs assigned to transactions that are not yet committed. The DBMS traverses a linked list of log entries that identifies a chronological history of transactions performed on the same row. The DBMS infers that the table row currently contains data stored by the most recently logged transaction that is not contained in the TSN image and that has thus been committed. The DBMS then continues to process statements of the transaction based on the assumption that the row contains the inferred value. The DBMS performs this procedure without acquiring a shared lock on the data page or on the index leaf page that points to the table row.

In one example, a computer implemented method may include retrieving resource definition data corresponding to an endpoint. The resource definition data includes adapter information and resource type information. Further, an adapter instance may be generated using the adapter information to establish communication with the endpoint. Furthermore, an API response may be obtained, via the adapter instance, from the endpoint by querying the endpoint using an API call. Further, the API response may be parsed. Further, a resource model corresponding to the resource definition data may be populated using the parsed API response. The resource model may include resource information and associated metric information corresponding to a resource type in the resource type information. Furthermore, a resource and/or metric data associated with the resource may be determined using the populated resource model. The resource may be associated with an application being executed in the endpoint.

A computer-implemented system for dynamic aggregation of data and minimization of data loss is disclosed. The system may be configured to perform instructions for: aggregating information from a plurality of networked systems by collecting a set of data from the networked systems, the set of data comprising data associated with a predetermined period of time and comprising one or more central variables that are included in data associated with more than one networked systems of the plurality of networked systems and one or more associated variables that describe one or more aspects of the central variables; retrieving one or more data transformation rules based on a relational map among the central variables and the associated variables; and aggregating the first set of data into one or more master data structures corresponding to the central variables based on the data transformation rules.

A method includes calculating first connection usage information based on a first number of connections being used in a connection pool over a first time interval and adding a first number of database connections to the connection pool based on determining that the first connection usage information satisfies a first usage threshold. Additionally, the method includes calculating second connection usage information based on a second number of connections being used in the connection pool over a second interval. The second interval has been previously reset responsive to adding the first number of database connections to the connection pool. The method also includes determining whether to adjust the number of database connections in the connection pool based on the second connection usage information.

A cloud computing system, which works in cooperation with a plurality of relay devices, is configured to receive measurement data transmitted from each of the relay devices arranged in respective bases and perform accumulation processing in a hierarchical structure of a logical tree form in a measurement database, and perform aggregation analysis processing on the measurement data subjected to the accumulation processing in the respective bases and for each integration target between the bases. The aggregation analysis processing is performed on the measurement data for the each integration target between the bases by recognizing a relationship between the bases under the same starting point on the basis of a measurement unit of a measurement value or a type of a measurement source as for the value in the source accumulated in the database as an ending point of the hierarchical structure.