Low-latency predictive database analysis

Patent metadata

Field	Value
Publication number	US-12554740-B2
Application number	US-202318186228-A
Country	US
Kind code	B2
Filing date	Mar 20, 2023
Priority date	Nov 13, 2018
Publication date	Feb 17, 2026
Grant date	Feb 17, 2026

Abstract

Low-latency autonomous-analysis includes obtaining data expressing a usage intent with respect to a low-latency database analysis system that intent omits data corresponding to user input expressly requesting low-latency autonomous-analysis, obtaining requested results data based on the data expressing the usage intent, outputting requested visualization data representing at least a portion of the requested results data for presentation to a user, and, in response to outputting the requested visualization data, obtaining low-latency autonomous-analysis data by performing low-latency autonomous-analysis based on the data expressing the usage intent by identifying an autonomous-analysis predicate based on the requested visualization data, obtaining a defined autonomous-analysis latency constraint, obtaining the low-latency autonomous-analysis data based on the autonomous-analysis predicate in accordance with the defined autonomous-analysis latency constraint, such that the low-latency autonomous-analysis data differs from the requested results data, and outputting at least a portion of the low-latency autonomous-analysis data for presentation to a user.

First claim

What is claimed is:

1 . A method comprising:
in response to outputting requested results data responsive to a request for data and absent user input data expressly requesting autonomous analysis, obtaining autonomous analysis data in accordance with the request for data and in accordance with a defined autonomous-analysis latency constraint, wherein the autonomous analysis data differs from the requested results data, wherein:
outputting the requested results data includes:
obtaining the request for data;
obtaining the requested results data in accordance with the request for data; and
outputting requested visualization data representing at least a portion of the requested results data for presentation to a user;

obtaining the autonomous analysis data includes:
identifying an autonomous-analysis predicate based on the requested visualization data; and
obtaining the autonomous analysis data in accordance with the autonomous-analysis predicate; and

in response to a determination that the request for data omits an expressly-specified request for data, an expressly-specified request for objects, and a requested object identifier:
obtaining the requested results data includes:
identifying previously generated objects based on the request for data; and
including, in the requested results data, requested results data portions respectively representing the previously generated objects;

outputting the requested visualization data includes including, in the requested visualization data, requested visualization data portions, wherein a requested visualization data portion from the requested visualization data portions is based on a respective requested results data portion from the requested results data portions and represents a corresponding previously generated object from the previously generated objects; and
identifying the autonomous-analysis predicate includes identifying a plurality of autonomous-analysis predicates, such that an autonomous-analysis predicate from the plurality of autonomous-analysis predicates corresponds to a respective requested visualization data portion from the requested visualization data portions; and

outputting at least a portion of the autonomous analysis data for presentation to the user.

2 . The method of claim 1 , wherein obtaining the autonomous analysis data includes:
identifying measure objects, wherein identifying the measure objects includes:
in response to a determination that the autonomous-analysis predicate includes a requested measure, including the requested measure in the measure objects; and
in response to a determination that the autonomous-analysis predicate omits the requested measure:
identifying a requested attribute from the autonomous-analysis predicate;
identifying exploratory measures based on the requested attribute and in accordance with the defined autonomous-analysis latency constraint, wherein identifying the exploratory measures includes identifying probabilistic utility data corresponding to respective exploratory measures; and
including the exploratory measures in the measure objects; and identifying attribute objects, wherein identifying the attribute objects includes:
in response to a determination that the autonomous-analysis predicate includes the requested attribute, including the requested attribute in the attribute objects;

identifying exploratory attributes based on the measure objects and in accordance with the defined autonomous-analysis latency constraint, wherein identifying the exploratory attributes includes identifying probabilistic utility data corresponding to respective exploratory attributes; and including the exploratory attributes in the attribute objects.

3 . The method of claim 2 , wherein in response to a determination that the defined autonomous-analysis latency constraint indicates a maximum cardinality of exploratory measures, identifying the exploratory measures includes identifying up to the maximum cardinality of exploratory measures from a plurality of available measures such that a probabilistic utility of the exploratory measures is maximal.

4 . The method of claim 2 , wherein in response to a determination that the defined autonomous-analysis latency constraint indicates a maximum cardinality of exploratory attributes, identifying the exploratory attributes includes identifying up to the maximum cardinality of exploratory attributes from a plurality of available attributes such that a probabilistic utility of the exploratory attributes is maximal.

5 . The method of claim 2 , wherein obtaining the autonomous analysis data includes:
obtaining autonomous-analysis insight data based on the measure objects and the attribute objects such that the autonomous-analysis insight data includes autonomous-analysis data other than the requested results data; and in response to a determination that the request for data is an expressly-specified request for data, obtaining autonomous-analysis related-request data based on the measure objects and the attribute objects such that the autonomous-analysis related-request data includes a resolved-request that differs from a resolved-request corresponding to the expressly-specified request for data.

6 . The method of claim 5 , wherein obtaining the autonomous-analysis insight data includes:
in response to a determination that the defined autonomous-analysis latency constraint indicates a defined maximum cardinality of outlier autonomous-analysis insight datasets, automatically generating outlier autonomous-analysis insight datasets up to the defined maximum cardinality of outlier autonomous-analysis insight datasets; in response to a determination that the defined autonomous-analysis latency constraint indicates a defined maximum cardinality of trend autonomous-analysis insight datasets, automatically generating trend autonomous-analysis insight datasets up to the defined maximum cardinality of trend autonomous-analysis insight datasets; in response to a determination that the defined autonomous-analysis latency constraint indicates a defined maximum cardinality of cross-correlation autonomous-analysis insight datasets, automatically generating cross-correlation autonomous-analysis insight datasets up to the defined maximum cardinality of cross-correlation autonomous-analysis insight datasets; in response to a determination that the defined autonomous-analysis latency constraint indicates a defined maximum cardinality of comparative autonomous-analysis insight datasets, automatically generating comparative autonomous-analysis insight datasets up to the defined maximum cardinality of comparative autonomous-analysis insight datasets; and in response to a determination that the defined autonomous-analysis latency constraint indicates a defined exploratory results constraint, obtaining exploratory results in accordance with the defined exploratory results constraint.

7 . The method of claim 1 , wherein outputting the portion of the autonomous analysis data includes:
generating a first object representing the portion of the autonomous analysis data, such that the first object includes a resolved-request corresponding to the portion of the autonomous analysis data.

8 . The method of claim 7 , further comprising:
outputting second requested results data for presentation to a user, wherein outputting the second requested results data includes:
obtaining the second requested results data, wherein obtaining the second requested results data includes:
obtaining a second request for data indicating the first object; and
obtaining the second requested results data in accordance with the first object;

in response to outputting the second requested results data and absent user input dat

Assignees

• Thoughtspot Inc

Inventors

• Agrawal Sanjay
• Jha Gunjan
• Chen Antony Chuxiao

Classifications

• G06F16/245

  Query processing · CPC title

• G06F16/248

  Presentation of query results · CPC title

• G06F16/2457

  with adaptation to user needs · CPC title

• G06F16/2428

  Query predicate definition using graphical user interfaces, including menus and forms (G06F16/2423 takes precedence) · CPC title

• G06F16/26 Primary

  Visual data mining; Browsing structured data · CPC title