Conquer Data Quality Challenges in 4 Steps – Phases 1-4

Author(s): Daniel Ko, Kolade Odetoyinbo, Dylan Browne

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Poor data quality is an ever-present challenge facing virtually every organization. This blueprint will help you establish a comprehensive strategy to remedy your most pressing data quality issues by following our four-phase methodology:

  1. Develop a Business-Driven Data Quality Improvement Plan
  2. Perform an In-Depth Data Assessment
  3. Assess Your Data Quality Practice
  4. Develop a Data Quality Roadmap for Continual Improvement

This blueprint will help you create and implement an effective data quality improvement initiative that is rooted in business-relevant use cases, as well providing a repeatable methodology that you can leverage to incrementally build an enterprise-wide data quality practice.

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