Structural Differences and Data Matching

Blog Administrator | Address Quality, Address Standardization, Data Cleansing, Data Enhancement, Data Enrichment, Data Governance, Data Integration, Data Management, Data Matching, Data Quality, Duplicate Elimination, Fuzzy Matching | , , ,

By David Loshin

Data matching is easy when the values are exact, but there are different types of variation that complicate matters. Let’s start at the foundation: structural differences in the ways that two data sets represent the same concepts. For example, early application systems used data files that were relatively “wide,” capturing a lot of information in each record, but with a lot of duplication.
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