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

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15 Parsing and Standardization

Chapter outline

  • 15.1 Data Error Paradigms 262
  • 15.2 The Role of Metadata 264
  • 15.3 Tokens: Units of Meaning 266
  • 15.4 Parsing 268
  • 15.5 Standardization 270
  • 15.6 Defining Rules and Recommending Transformations 272
  • 15.7 The Proactive versus Reactive Paradox 275
  • 15.8 Integrating Data Transformations into the Application Framework 277
  • 15.9 Summary 277

As discussed in chapter 13, proactive data quality management concentrates on inspection, monitoring, and ultimately prevention. Instituting inspection and monitoring for potential anomalies is a way of flagging issues when they occur, identifying the source of error introduction, and facilitating the elimination of the root cause. However, there are certain situations ...

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