12 actions to improve data quality

Improving data quality is an ongoing effort

Gartner, Inc. has identified 12 actions that can help Chief Data and Analytics Officers (CDAOs) and other Data and Analytics (D&A) leaders improve data quality (DQ) within their organizations. These actions are aimed at avoiding high costs and delivering sustainable value. Jason Medd, a Director Analyst at Gartner, emphasizes that data quality issues can be costly but can also be fixed relatively easily and quickly. He advises CDAOs to establish impactful and supportive DQ programs to prevent complications and missed opportunities.

Improving data quality is an ongoing effort, and Medd cautions against taking a technology-centric approach without considering organizational culture, people, and processes. Gartner analysts predict that by 2024, 50 per cent of organizations will adopt modern DQ solutions to better support their digital business initiatives.

At the Gartner Data & Analytics Summit, the analysts shared 12 actions grouped into four categories to help CDAOs prioritize their efforts based on problem areas. Here are the four categories:

  • Focus on the Right Things to Set Strong Foundations:
    • Identify and prioritize the most influential data on business outcomes.
    • Understand key performance indicators (KPIs) and key risk indicators (KRIs).
    • Build a business case and establish common DQ language and standards.
  • Apply Data Quality Accountability:
    • Obtain sponsorship from the D&A governance committee.
    • Dedicate data stewards from business units and the central D&A team.
    • Form special interest groups to benefit from DQ improvement and share best practices.
  • Establish “Fit for Purpose” Data Quality:
    • Perform data profiling and monitoring to identify gaps and challenges.
    • Develop improvement plans and transition to a governance model based on trust.
    • Drive enterprise-wide adoption of DQ initiatives.
  • Integrate Data Quality into Corporate Culture:
    • Leverage technology to reduce manual efforts and obtain faster results.
    • Identify and address frequent DQ issues within business workflows.
    • Improve data literacy across the organization, establish a DQ culture, and facilitate knowledge sharing and collaboration.

By following these actions, CDAOs can enhance data quality and ensure its integration into the corporate culture, leading to improved business outcomes and reduced risks.



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