Google Inc.

Jamie Davidson

Palash Nandy

Benjamin Liebald

Christina Ilvento

Colin Zima

Dasarathi Sampath

Jonathan Swenson

Patrick Hung

Ye Niu

Julian Hyde

Wil Gieseler

Lloyd Tabb

Steven Talbot

Conrad Slimmer

Ben Porterfield

Extending access to a data model includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

Extension framework for data analytics

A method for the automatic generation of a data model from an SQL statement includes receiving a single SQL statement in a user interface to a data analytics application, parsing the single SQL statement and extracting from the SQL statement different table references. The method also includes, for each one of the table references, directing a selection of all fields available in a corresponding table and storing the available fields in a collection of fields implicated by each table referenced by the table references. Finally, the method includes generating a data model with the fields in the collection of fields and displaying a view of the data model in a user interface of the data analytics application.

Automatic generation of a data model from a structured query language (SQL) statement

Data content governance for presentation layer synchronization for a version controlled underlying data model includes defining a data model for underlying data in a database, specifying a presentation layer for the defined data model and identifying selected elements of the data model necessary to meet data requirements of the specified presentation layer. Then, the identified selected elements of the data model are serialized and both the specified presentation layer and the serialized elements are versioned in respect to the specified presentation layer. Thereafter, when the data model becomes modified, the specified presentation layer is modified to accommodate the modified data model. In response to the modification, a different selection of elements of the data model necessary to meet data requirements of the modified presentation layer are re-identified and serialized, with the modified presentation layer and the serialized re-identified different selection of elements becoming re-versioned.

Data content governance for presentation layer synchronization for a version controlled underlying data model

Extending access to a data model in a data analytics computer data processing system includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are stored in association with the user profile.

Topic based user profiles

A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

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San Francisco, CA, United States of America

Jamie Davidson