Open AccessExceptional Data Quality Using Intelligent Matching and Retrieval
Author(s) -
Bidlack Clint,
Wellman Michael P.
Publication year - 2010
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v31i1.2280
Subject(s) - computer science , matching (statistics) , quality (philosophy) , data quality , software , blossom algorithm , data mining , database , information retrieval , data science , marketing , business , programming language , metric (unit) , philosophy , statistics , mathematics , epistemology
Recent advances in enterprise web‐based software have created a need for sophisticated yet user‐friendly data‐quality solutions. A new category of data‐quality solutions that fill this need using intelligent matching and retrieval algorithms is discussed. Solutions are focused on customer and sales data and include realtime inexact search, batch processing, and data migration. Users are empowered to maintain higher quality data resulting in more efficient sales and marketing operations. Sales managers spend more time with customers and less time managing data.