Salesforce Com, Inc.

Salesforce, Inc.

Tableau Software, Inc.

James Diefenderfer

Zuye Zheng

Khushboo Shah

Sandeep Rawat

Dylan Thom

Ravishankar Arivazhagan

Ryoji Osawa

Vandit Garg

Wenying Yang

Pragya Anand

Niranjan Yadavali

Vaibhav Garg

Katherine Jeanne Rushton

Srividhya Agandeswaran

Nadeem Marfani Aboobaker

Deepinder Badesha

Andrew Son Nhat Tran

Irene Fung

Julian Navaratnam

Martin Desrosiers

Si Wan Kim

Saloni Shah

Shaila Shree

Yaoyao Lin

Sreevatson Mahabalipuram Chakravarthy

Anirudh Sridhar

Nadeem Aboobaker

Danny Lai

Khushboo Bharat Shah

Sameer Sethi

Praveen Pendey

A computing device receives a first user interaction with a graphical user interface (GUI) of the computing device. In response to the user interaction, the device sends, to a server system, a request for data corresponding to a first component of the GUI. The device initializes the first component concurrently with the sending. The device receives, from the server system, the data corresponding to the first component and corresponding metadata for the first component. The device generates the first component based on the corresponding metadata and at least a first subset of the received data and displays the first component in a first portion of the GUI. Concurrently with the generating and displaying, the device generates a second component of the GUI based on at least a second subset of the received data, and displays the second component simultaneously with the first component.

Embedding scalable CRM dashboards in transactional pages

Methods, systems, and devices supporting primitive-based query generation are described. A database system may receive a natural language query associated with a subset of data sets stored at the database system, determine a set of tokens included in the natural language query, and label one or more tokens of the set of tokens with one or more primitives from a set of supported primitives associated with the subset of data sets. The database system may determine a set of higher order concepts corresponding to query operations, query conditions, or both based on the one or more labeled tokens. The database system may train a neural network to learn a grammatical structure of the natural language query and generate a database query for querying the database system based on the one or more labeled tokens, the set of higher order concepts, and the neural network.

Primitive-based query generation from natural language queries

The various implementations described herein include methods and devices for using a messaging system to analyze and distribute data analytics. In one aspect, a method includes displaying a user interface for a communications application, the user interface including a dashboard display area for a group of users. In response to a user input, display of the dashboard display area is replaced with a view corresponding to a data analysis application. The data analysis application is separate from the communications application, and the view corresponding to the data analysis application provides access to reports generated, using credentials of a user of the communications application, without user input to execute or open the data analysis application. A second user input is received requesting to share a report with the selected group of users, and in response, the report is published to the dashboard display area for the selected group of users.

Using a communications application to analyze and distribute data analytics

Methods, systems, and devices supporting querying disparate data sources are described. Querying disparate data sources may include receiving an input for data stored at a first data source from a plurality of data sources, selecting a first data connector from a plurality of data connectors, wherein the first data connector corresponds to the first data source, and identifying a first query language corresponding to the first data source from a plurality of query languages. Querying the disparate data sources may further include generating a converted query based at least in part on the first query language and retrieving the data from the first data source using the first data connector based at least in part on the converted query.

Query conversion for querying disparate data sources

Systems, methods, and computer-readable media for implementing a modulate runtime environment (MRTE) are described. The MRTE includes multiple layers that communicate with one another using messages that are routed by connectors. A computer system may implement an MTRE that includes a platform-specific visualization layer and a data layer, which may include a headless execution engine. The data layer may be implemented by multiple types of computing platforms, and the platform-specific visualization layer may be replaced for different computing platforms. Other embodiments may be described and/or claimed.

Modular runtime environment

A database system may include a data storage configured to store one or more data sets and a processor coupled to the data storage. The processor may receive a query for first data included in the one or more data sets and access the data storage to obtain the first data based on the query. The processor may transmit the first data to a user system. The processor may receive an indication of a filter request to filter the first data based on a characteristic. The processor may identify linked data within second data based on the characteristic, the linked data linked to a portion of the first data associated with the filter request. The processor may access the data storage to obtain the linked data and transmit the linked data to the user system, to enable updating of a data presentation to display the linked data.

Filter of data presentations via user-generated links

A user system includes a user interface, a processor, and one or more stored sequences of instructions. The one or more stored sequences of instructions, when executed by the processor, cause the processor to display a script field within an editor dashboard, of a runtime environment, displayed on the user interface, the editor dashboard configured to define an interactive dashboard of the runtime environment, identify a script entry input into the script field, parse the script entry to identify an operation to be performed within the interactive dashboard in response to a trigger event, and associate the operation with the interactive dashboard, so that the operation will be performed within the interactive dashboard in response to the trigger event based on the association.

Dashboard execution engine

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San Francisco, CA, United States of America

James Diefenderfer