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The Practitioner's Guide to Data Quality Improvement by David Loshin

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16 Entity Identity Resolution

Chapter outline

  • 16.1 The Lure of Data Correction 280
  • 16.2 The Dual Challenge of Unique Identity 281
  • 16.3 What Is an Entity? 282
  • 16.4 Identifying Attributes 283
  • 16.5 Similarity Analysis and the Matching Process 285
  • 16.6 Matching Algorithms 286
  • 16.7 False Positives, False Negatives, and Thresholding 289
  • 16.8 Survivorship 291
  • 16.9 Monitoring Linkage and Survivorship 293
  • 16.10 Entity Search and Match and Computational Complexity 293
  • 16.11 Applications of Identity Resolution 294
  • 16.12 Evaluating Business Needs 296
  • 16.13 Summary 296

Both the data quality assessment process and analyses driven by the desire for unifying and consolidating multiple sources of data are likely to expose many situations in which there is ...

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