Tableau Software, Inc.

Salesforce, Inc.

Yukiko Ishida Anonuevo

Ryan Andrew Atallah

Jared Briskman

Alex Djalali

Suyang Duan

Qixiang Zhang

Sophia Chen

Bailiang Zhou

Amar Singh Lakhian

Manish Tripathi

Andre Lukas Schorlemmer

Kartik Sundar

Naomi Menahem

Katherine Anne Maertens

The various implementations described herein include methods and devices for providing an instant messaging interface for data analytics. In one aspect, a method includes displaying a user interface for a communication application, including displaying a shared link to a graphical data visualization. A snapshot button near the link is used to generate a link snapshot comprising a version of the graphical data visualization. In response to user activation of the snapshot button, the method generates the link snapshot. To generate the link snapshot the method first determines if the user or users have proper security access to view the data contained in the graphical data visualization. If a user has proper security access to a subset of the data from the data source, the method dynamically generates the link snapshot for the subset of data to which the user has security access.

Providing an instant messaging interface for data analytics

A method generates data analysis templates. A computing device receives, via a graphical user interface, a natural language input, which includes multiple terms. The terms include one or more data fields and/or data values from a data source. The device designates the natural language input as trigger text for a data analysis template. The trigger text includes the multiple terms. A user defines one or more rules for a subset of the terms, each rule specifying respective criteria to match a respective term in the subset. A user specifies multiple data visualizations corresponding to the trigger text. Each of the data visualizations (i) uses a respective one or more data fields, from the data source, corresponding to terms from the trigger text and (ii) has a respective data visualization type. The device generates the data analysis template according to the trigger text, the user definition, and the user specification.

Generating data analysis dashboard templates for selected data sources

The various implementations described herein include methods and devices for recommending phrases for data visualizations. In one aspect, a method includes presenting a data visualization page to a user, the page including a first region for displaying a data visualization and a second region for phrase recommendations. The method further includes obtaining a dataset selected by the user, the dataset including a plurality of fields; and generating a first set of phrase recommendations based on the dataset, each phrase recommendation corresponding to a respective field. The method also includes displaying the first set of phrase recommendations in the second region; and receiving a user selection of a first phrase. The method further includes, in response to the user selection: presenting a data visualization in the first region using the first phrase; and displaying a second set of phrase recommendations generated based on the first phrase.

Phrase recommendations for data visualizations

A computer system receives from a messaging system a first input commencing an analytic conversation between the computer system and an electronic device. The messaging system is communicatively connected with the electronic device and executes a messaging application on the electronic device. The computer system identifies a data source corresponding to the analytic conversation. The computing system receives from the messaging system a second input specifying a natural language command related to the data source. The computer system generates an interpretation corresponding to the natural language command and queries the data source according to the interpretation. The computer system generates a first data visualization using a first subset of data fields from the data source and sends a first representation of the first data visualization to the messaging system, for display on the electronic device.

Conversational natural language interfaces for data analysis

The various implementations described herein include methods and devices for constructing phrases for data visualizations. In one aspect, a method includes presenting a data visualization page to a user including a visualization region and a phrase region; obtaining a dataset including a plurality of fields; displaying a phrase affordance for constructing a phrase; in response to a user selection of the phrase affordance, presenting a phrase construction menu including a set of fields; in response to a user selection of a field, presenting a set of aggregation operators selected based on a field type of the field; in response to a user selection of an aggregation operator, generating a first phrase using the selected field and the selected aggregation operator; presenting a data visualization generated using the first phrase; and displaying the first phrase as an active phrase in the phrase region.

Phrase builder for data analytic natural language interface

A computing device receives from a user a partial natural language input related to a data source. The computing device receives an additional keystroke corresponding to the partial natural language input. The partial natural language input and the additional keystroke comprise a character string. In response to the additional keystroke, the computing device generates one or more interpretations corresponding to entities in the data source. The computing device displays the interpretations. In some implementation, the character string comprises a sequence of terms, and the device displays the interpretations in a dropdown menu adjacent to the most recently entered term in the sequence. In some implementations, the dropdown menu includes a plurality of rows, each row displaying a respective data value and a respective data field corresponding to the respective data value. Some implementations display a statistical distribution of data values for a data field (displayed adjacent to the first interpretation).

Using dynamic entity search during entry of natural language commands for visual data analysis

A computing system receives from a messaging system a first input identifying a data source. The computing system receives from the messaging system a second input specifying a natural language command related to the data source. The system translates the second input into a set of parameters for building a first data visualization from the data source. The system calls one or more API functions provided by a data visualization server, and the computing system receives from the data visualization server a first data visualization that includes a first subset of data fields from the data source. The system generates a representation of the first data visualization and sends the representation to the messaging system, which in turn sends the representation to an electronic device for display on the device.

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Concord, CA, United States of America

Yukiko Ishida Anonuevo