Get it Right the First Time

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Data Quality, Data Quality Assessment | , , , , ,

By Elliot King

People generally think of data quality as a remedial exercise. During the ongoing course of business, for a variety of reasons, companies find themselves with incorrect data. The goal of a data quality program is to identify the incorrect data and fix it.
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Normalizing Structure Using Data Standardization for Improved Matching

Blog Administrator | Address Quality, Address Standardization, Analyzing Data, Data Matching, Data Quality, Record Linkage | , , , , , ,

By David Loshin

In my last few posts, I discussed how structural
differences impact the ability to search and match records across different
data sets. Fortunately, most data quality tool suites use integrated parsing
and standardization algorithms to map structures together.
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Data Quality Management Mistakes to Avoid

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By Elliot King

Everyone wants high quality data and it seems that goal should not be so hard to achieve. The need seems obvious and there are plenty of good tools that can be put to work in the effort. Unfortunately, it is just not that easy to set up a successful, ongoing data quality program.
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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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Moving to Action

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Data Cleansing, Data Quality, Data Quality Assessment | , , , , , , ,

By Elliot King

The first step in a data quality program is to assess your data. Whether you opt for data profiling or some other assessment mechanism, this part of the process consists of systematically identifying exactly where the problems can be found in your data sets.
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