Teresa Lynn Roberts

US Patent:

20200125239, Apr 23, 2020

Filed:

Dec 30, 2018

Appl. No.:

16/236612

Inventors:

- Seattle WA, US
Roger Hau - Seattle WA, US
Daniel Cory - Seattle WA, US
Jiyoung Oh - San Carlos CA, US
Teresa Roberts - Palo Alto CA, US

International Classification:

G06F 3/0484
G06F 16/28
G06F 16/248
G06F 16/22
G06F 16/2455

Abstract:

The method receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with data fields and each data field is a dimension or a measure. The method forms dimension tuples comprising distinct ordered combinations of data values for the dimensions D. For each measure, the method: forms a set S of the dimensions D plus dimensions from a primary key corresponding to the measure; retrieves intermediate tuples containing the fields in S and the measure, without aggregation; and aggregates the intermediate tuples according to the dimensions D. For each dimension tuple, the method forms an extended tuple by appending the aggregated data values corresponding to each measure field. The method then builds and displays a data visualization according to the extended tuples and the visual variables to which the data fields are associated.

US Patent:

20200125559, Apr 23, 2020

Filed:

Dec 30, 2018

Appl. No.:

16/236611

Inventors:

- Seattle WA, US
Roger Hau - Seattle WA, US
Daniel Cory - Seattle WA, US
Jiyoung Oh - San Carlos CA, US
Teresa Roberts - Palo Alto CA, US

International Classification:

G06F 16/248
G06F 16/26
G06F 16/242

Abstract:

The method receives a visual specification, which specifies a data source, visual variables, and data fields from the data source. Each visual variable is associated with data fields and each data field is either a dimension or a measure. From an object model of the data source, the method identifies a minimal subtree that includes all of the dimension data fields and constructs a query from the minimal subtree. The method executes the query against the data source to retrieve a set of tuples, each tuple comprising a unique ordered combination of data values for the dimension data fields. For each tuple, the method forms an extended tuple by appending aggregated data values corresponding to each measure data field. The method then builds and displays a data visualization according to the data fields in the extended tuples and according to the visual variables to which the data fields are associated.