US 2019/0197168 A1 · CONTEXTUAL ENGINE FOR DATA VISUALIZATION

Abstract

Systems, methods, and computer program products are disclosed for providing a contextual recommendation corresponding to a visualization. An example method includes ingesting a data set from or more data sources, including applying rules that transform the data set into a standardized format. The subsets of the ingested data set are assigned based on a determined variable into population coverage ranges that correspond to statistical distributions of the determined variable. Distribution analysis is performed across at least one of the population coverage ranges to identify a distribution data set corresponding to the determined variable. The distribution set is parsed to identify a context recommendation. The identified context recommendation is mapped to a tag corresponding to the determined variable, and a visualization type corresponding to the distribution data set. The tag, the context recommendation, and the visualization type are ranked, and a rendered visualization is then provided, to a graphical user interface, corresponding to the ranked tag, the ranked context recommendation, and the ranked visualization type.

Claims20

Dependent claims

A system, comprising:

a non-transitory memory;
and
one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising:
ingesting a data set from or more data sources, the ingesting including applying rules that transform the data set into a first format;
assigning, based on a determined variable, subsets of the ingested data set into population coverage ranges that correspond to statistical distributions of the determined variable;
identifying, by performing distribution analysis across at least one of the population coverage ranges, a distribution data set corresponding to the determined variable;
parsing the distribution set to identify a context recommendation;
mapping the identified context recommendation to a tag corresponding to the determined variable, and a visualization type corresponding to the distribution data set;
ranking the tag, the context recommendation, and the visualization type;
and
providing, to a graphical user interface, a rendered visualization corresponding to the ranked tag, the ranked context recommendation, and the ranked visualization type.

8 more elements

A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising:

ingesting a data set from or more data sources, the ingesting including applying rules that standardize the data set;
assigning, based on a determined variable, the ingested data set into population coverage ranges that correspond to statistical distributions of the determined variable;
identifying, by performing distribution analysis across at least one of the population coverage ranges, a distribution data set corresponding to the determined variable;
parsing the distribution set to identify a context recommendation;
mapping the identified context recommendation to a tag corresponding to the determined variable, and a visualization type corresponding to the distribution data set;
ranking the tag, the context recommendation, and the visualization type;
and
providing, to a graphical user interface, a rendered visualization corresponding to the ranked tag, the ranked context recommendation, and the ranked visualization type.

5 more elements

A method comprising:

transforming a data set into a first format;
assigning, based on a variable determined from a hypothesis provided by a user, subsets of the transformed data set into population coverage ranges that correspond to statistical distributions of the determined variable;
identifying, by performing distribution analysis across at least one of the population coverage ranges, a distribution data set corresponding to the determined variable;
parsing the distribution set to identify a context recommendation;
mapping the identified context recommendation to a tag corresponding to the determined variable, and a visualization type corresponding to the distribution data set;
ranking the tag, the context recommendation, and the visualization type;
and
providing, to a graphical user interface, a rendered visualization corresponding to the ranked tag, the ranked context recommendation, and the ranked visualization type.

5 more elements

Dependencies are inferred from the claim text.

Contextual engine for data visualization

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Contextual engine for data visualization

Life of this patent

Abstract

Claims20