Provided are systems and methods directed to identifying relationships between colloquial place names in a relational database. In some embodiments, a method of identifying relationships between colloquial place names in a relational database comprises receiving geographic location information; generating a vector corresponding to the geographic location; comparing the geographic location information vector to a plurality of colloquial place name vectors in a relational database that maps a plurality of colloquial place names to a plurality of corresponding colloquial place name vectors in a vector space, to generate a plurality of similarity scores that is calculated based on the geographic location information vector and each colloquial place name vector of the plurality of colloquial place name vectors; and identifying that one or more colloquial place names in the relational database are related to the geographic location information based on the plurality of similarity scores.

Provide is a visualization system that enables generation of a “dashboard” of individual visualizations. In further embodiments, the system enables users to quickly and easily generate these visualizations and integrate complex filters, queries, aggregations, etc., with simple UI input. The visualizations can be provided as a service that requests information from an underlying database. The database itself may also be hosted as a service, permitting granular and native database functions layered with the visualization architecture. The system can support additional functionality and access management to generate visualizations that can be shared with other users and/or integrated into websites, blogs, etc. The system can handle the complex logic, data interactions, dynamic data transformation, dynamic authorization, etc., needed to manage data rules (e.g., access rules layered over database permission based control, summarization/aggregation requirements, etc.) for any data being rendered in individual visualization and/or the dashboard of multiple visualizations.

A method includes receiving a spreadsheet file representing a plurality of decision tables, wherein the spreadsheet file does not indicate dependencies between non-labeled inputs and non-labeled outputs of the plurality of decision tables. The method further includes, for a first decision table of the plurality of decision tables, identifying, in view of an identifier of a second decision table of the plurality of decision tables, a dependent input that comprises an output of the second decision table of the plurality of decision tables. The method further includes determining, by a processing device, in view of an ordering of columns in the spreadsheet file, remaining inputs and outputs of the first decision table.

A filter request for a data set indicates a query specification and one or more sub-range indicators of a disjoint subset descriptor. Corresponding the individual data records obtained from the data set using the query specification, a respective range mapping value is generated. Using the range mapping values and the sub-range indicators, a result set of the filter request is obtained.

Techniques are provided for generating score(s) and/or correction(s) for a digital twin representing a utility network. One or more bridges transform data, from a plurality of system and associated with a utility network, to a different format, e.g., relational database format. A process generates a digital twin of the utility network utilizing the data in the different format. A data quality service (DQS) performs evaluations and/or analyses of the digital twin to generate a baseline score and an updated score representing a state of the digital twin if corrections are applied. If the updated score meets or is above a threshold value, the DQS automatically applies and save the corrections to the digital twin. If the updated score does not meet the threshold value, the DQS presents a failure notification and one or more graphical representations of the utility network such that incremental corrections can be made.

Provide is a visualization system that enables generation of a “dashboard” of individual visualizations. In further embodiments, the system enables users to quickly and easily generate these visualizations and integrate complex filters, queries, aggregations, etc., with simple UI input. The visualizations can be provided as a service that requests information from an underlying database. The database itself may also be hosted as a service, permitting granular and native database functions layered with the visualization architecture. The system can support additional functionality and access management to generate visualizations that can be shared with other users and/or integrated into websites, blogs, etc. The system can handle the complex logic, data interactions, dynamic data transformation, dynamic authorization, etc., needed to manage data rules (e.g., access rules layered over database permission based control, summarization/aggregation requirements, etc.) for any data being rendered in individual visualization and/or the dashboard of multiple visualizations.

A computer-implemented method includes: reading a vector of a first table in a database, the vector including counts of a plurality of keywords in the first table, the plurality of keywords including a first keyword and a second keyword; determining a first custom attribute describing the first table, the first custom attribute having a vector including counts of at least a first portion of the plurality of keywords in the first table; determining a multiplier of the first custom attribute, the multiplier being a number of other tables that reference the first custom attribute; and revising the vector of the first table based on the first custom attribute.

Technology is described for processing Internet of Things (IoT) device data. IoT device data may be received from an IoT device. Contextual data that is related to the IoT device data from the IoT device may be identified. A first schema that defines the IoT device data and a second schema that defines the contextual data may be identified. A relational database that merges the IoT device data with the contextual data may be created. Knowledge of the first schema and the second schema may enable the IoT device data and the contextual data to be read and organized in the relational database.

A Universal identification system comprising: a Universal ID device, a Universal ID reader and a Universal ID computing system is described.

A method may include (i) obtaining first data records structured in accordance with a first schema, (ii) determining, for the first schema, one or more first schema property values for each schema property in a set of pre-defined schema properties, (iii) determining, for a second schema, one of more second schema property values for each schema property in the set of pre-defined schema properties, (iv) providing, to a schema matching engine, first and second schema property values, where the schema matching engine contains schema mapping techniques and rules, where each rule suggests a schema mapping technique based on schema properties from the set of pre-defined schema properties, (v) applying the rules to select a schema mapping technique, (vi) transforming the first data records in accordance with the selected schema mapping technique, and (vii) providing the transformed first data records in a data structure in accordance with the second schema.