The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jun. 24, 2025
Filed:
Mar. 14, 2022
Adobe Inc., San Jose, CA (US);
Arpit Ajay Narechania, Atlanta, GA (US);
Fan Du, Milpitas, CA (US);
Atanu R. Sinha, Bangalore, IN;
Ryan A. Rossi, San Jose, CA (US);
Jane Elizabeth Hoffswell, Seattle, WA (US);
Shunan Guo, San Jose, CA (US);
Eunyee Koh, Sunnyvale, CA (US);
John Anderson, San Jose, CA (US);
Sonali Surange, San Rafael, CA (US);
Saurabh Mahapatra, Sunnyvale, CA (US);
Vasanthi Holtcamp, Fremont, CA (US);
Adobe Inc., San Jose, CA (US);
Abstract
Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: 'quality'—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle. For example, an interactive tree view may visually represent a nested attribute schema and attribute quality or consumption metrics to facilitate discovery of bad data before ingesting into a data lake.