Gartner Research

5 Steps to Build a Business Case for Continuous Data Quality Assurance

Published: 20 April 2020

ID: G00464486

Analyst(s): Saul Judah , Alan D. Duncan , Melody Chien , Ted Friedman


Data quality improvement is not a one-time activity. Data and analytics leaders, including chief data officers, must plan for ongoing improvement and assurance in their data quality business case if they wish to deliver sustainable value to their organization.

Table Of Contents
  • Key Challenges



  • Make People Care About Data Quality
    • Step 1: Expose the Pain Caused by Poor Data Quality
    • Step 2: Use Metrics to Prove the Impact of Poor Data Quality on Key Business Performance and Risk Indicators
  • Identify Root Causes of Poor Data Quality and Show How to Fix It
    • Step 3: Explore the Origins of Data Quality Issues and Triage Solution Scope Based on Prioritized Outcomes
    • Step 4: Define the Approach, Deliverables, Time Scales and Outcomes
  • Position Data Quality as an Ongoing Program of Work
    • Step 5: Complete the Financials and Create a Meaningful Story for Ongoing Data Quality Improvement

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