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

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14 Data Profiling

Chapter outline

  • 14.1 Application Contexts for Data Profiling 242
  • 14.2 Data Profiling: Algorithmic Techniques 245
  • 14.3 Data Reverse Engineering 248
  • 14.4 Analyzing Anomalies 249
  • 14.5 Data Quality Rule Discovery 251
  • 14.6 Metadata Compliance and Data Model Integrity 254
  • 14.7 Coordinating the Participants 256
  • 14.8 Selecting a Data Set for Analysis 257
  • 14.9 Summary 259

Data profiling has become such a ubiquitous piece of technology that it is often specifically equated with the concept of data quality assurance. And as data profiling has emerged as a critical commodity tool, it should be viewed as a set of technical tools that can be applied in support of numerous information management programs, including data quality assessment, ...

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