ThoughtSpot had six patents in digitalization during Q2 2024. ThoughtSpot Inc’s patents in Q2 2024 focus on innovative systems and methods for query generation based on logical data models with one-to-one joins, automatic data modeling based on usage intent, and operating a low-latency database analysis system with phrase translation. These technologies aim to improve data querying, analytical modeling, and database analysis processes for enhanced user experience and efficiency. GlobalData’s report on ThoughtSpot gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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ThoughtSpot had no grants in digitalization as a theme in Q2 2024.
Recent Patents
Application: Query generation based on a logical data model with one-to-one joins (Patent ID: US20240211479A1)
The patent filed by ThoughtSpot Inc. describes systems and methods for query generation based on a logical data model with one-to-one joins. The methods involve accessing a join graph representing tables in a database, selecting a connected subgraph that includes tables referenced in a query, modifying the subgraph based on one-to-one join indications, generating leaf queries, creating a query graph specifying joining results from leaf queries, and invoking a transformed query on the database. The claims detail a method for obtaining a database query, generating a transformed database agnostic representation, obtaining user input data, and automatically generating a database agnostic representation of the query. The method further involves transforming the representation based on relationship data, obtaining results data from the database, and outputting the data for user presentation.
The patent also includes claims related to the structure and functionality of a data analysis system that implements the described methods. The system comprises a memory and a processor that executes instructions to obtain a database query, generate a transformed representation, obtain user input data, and create a query graph based on a modified subgraph. Additional claims specify the cardinality of root vertices in the subgraph, determining omitted edges representing joins, and including non-root vertices in the query graph. The system is designed to automatically generate database agnostic representations of queries, handle one-to-one joins, and facilitate efficient data analysis and presentation to users.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
