Identifying and resolving data quality issues amongst information stored across multiple data sources

作者: Chappell Gregory Louis , Freiberg Ben Jannis , Butkovic Petar , Zotos Alexandros , Skevakis Giannis

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摘要: The techniques described herein are directed to identifying data quality issues within information stored across multiple different sources. For instance, the can comprise missing values, inconsistent and un-translated values. Once identified, implement actions resolve so that consumption or use of is improved. In at least one example, identification resolution a issue be implemented in response receiving query identifies an object. Based on query, system collect from sources, for attributes have been defined item. algorithms (e.g., comparison algorithm) identify output graphical user interface visually distinguishes between with without issue.

参考文章(20)
Carla Staeben, Bob Savard, Alex Wilbur, Cristina Maier, Method, apparatus, and computer program product for data quality analysis ,(2014)
Elisa Flasko, Lukasz Gwozdz, Maxim Uritsky, Robert M. Fries, Dataset rating and comparison ,(2011)
Fedja Hadzic, Michael Hecker, A method of analysing data ,(2012)
Narendar Yalamanchilli, Data extraction and testing method and system ,(2011)
Max Hrabrov, Jennifer Gromada, Aviv Orani, Sugandh Mehta, Cornelius Crowley, Matthew Rice, Guerney Holloway Hunt, Teresa Glasser, Ronald Adinolfi, Francis Parr, Multi-source multi-tenant entitlement enforcing data repository and method of operation ,(2005)
David Cronin, Franklin Jose, George Phillip, Randy Lynn Taylor, Alan Ferris James, David Edwards, Formlets as an enabler of the clinical user experience ,(2012)