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

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11 Data Quality Assessment

Chapter outline

  • 11.1 Planning 192
  • 11.2 Business Process Evaluation 194
  • 11.3 Preparation and Data Analysis 197
  • 11.4 Data Profiling and Analysis 199
  • 11.5 Synthesis of Analysis Results 202
  • 11.6 Review with Business Client 205
  • 11.7 Summary Rapid Data Assessment – Tangible Results 206

By now it should be clear that the absence of clearly defined measurements to demonstrate how business impacts are attributable to erred data prevents developing an appropriate business case for introducing data quality management improvement. When resources are allocated to correcting “bad data” without being able to evaluate the root causes, there is no ability to objectively evaluate the relationship between poor data quality and business ...

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