Trifacta Inc.

Leland Stanford Junior University

Sean Philip Kandel

Adam Silberstein

Philip John Vander Broek

Edward Eli Marschner

Alon Bartur

Wei Zheng

Jeffrey Heer

Aaron J Elmore

Chris Beavers

Joseph M Hellerstein

Andreas Paepcke

Lars Grammel

Hector Garcia-Molina

Zain Asgar

Martin Theobald

Eric S Abelson

A system standardizes values that occur in large datasets before the dataset is analyzed. The system identifies values in a dataset that are similar to each other and associates those values with each other to form groups. The system determines a canonical value for each group of associated values. Within each group, the system replaces values that have been associated with each other with the canonical value for the group. As a result, the dataset is transformed into a dataset that has standardized values, and the standardized dataset is provided as input for analysis by a data analysis system. By standardizing the dataset in this manner, the data analysis system can process a larger portion of the dataset.

Standardizing values of a dataset

A data preprocessing system builds transformation scripts for preprocessing datasets for processing by a data analysis system. The data preprocessing system presents various representations of data of a dataset including visual representations, textual representations, or structural representations. The data preprocessing system receives selections of attributes or values based on these representations. The data preprocessing system generates recommendations of transformations based on the attributes or values selected. The data preprocessing system builds a transformation script based on the recommendations of the transformations. The transformation script can be used for preprocessing the dataset for analysis by a data analysis system.

Visual interactions for transforming datasets with nested data structures

Transforming datasets with nested data structures

A system determines samples of datasets that are typically processed by big data analysis systems. The samples are for use for development and testing of transformations for preprocessing the datasets in preparation for analysis by big data systems. The system receives one or more transform operations input datasets for the transform operations. The system determines samples associated with the transform operations. According to a sampling strategy, the system determines samples that return at least a threshold number of records in the result set obtained by applying a transformation. According to another sampling strategy, the system receives criteria describing the result of the transform operations and determines sample sets that generate result sets satisfying the criteria as a result of applying the transform operations.

Sampling for preprocessing big data based on features of transformation results

Transformation based sampling for preprocessing big data

A system provides data profile information describing attributes of a dataset. The system determines relative frequency of occurrences of attribute values with respect to a set of bins from a histogram of another attribute. The system presents a user interface that presents statistical information describing attributes of a dataset based on the relative frequency of occurrences of attribute values. The system generates a transformation script based on the user interactions for transforming records of the dataset. The transformation script is configured to preprocess data of the dataset for further analysis.

Data profiling of large datasets

A system and method identifies rows in a file as uniform rows or outlier rows based on statistics from the file, and displays a sampling of uniform and outlier rows.

System and method for displaying a sample of uniform and outlier rows from a file

A system and method parses one or more fields from a file by receiving example locations of the field in the file, fashioning rules that describe the field from the locations, and then scoring the rules against some or all of the file.

System and method for identifying fields in a file using examples in the file received from a user

A system and method automatically identifies any or all of potential row, column and string delimiters in a file in which such delimiters are unknown to the program making such identification.

System and method for identifying delimiters in a computer file

A spreadsheet system stores objects and formulas in the cells of the spreadsheet, along with metadata tags. Each cell may contain multiple objects (such as a group of photos). Drag-and-drop user actions automatically change tags associated with the moved objects based on a formula stored in the target cell if a forcing semantics mode is active, or automatically change a formula stored in the target cell if a non-forcing semantics mode is active. A formula in a cell selects a set of objects and may include set operators such as union, intersection, and minus. The formula may also filter sets to select a subset based on specified tag attributes of objects. The display of the spreadsheet adaptively selects a subset of objects to render in a cell and appropriately scales photos for optimal viewing.

Growing community of inventors

San Francisco, CA, United States of America

Sean Philip Kandel