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How good are my data?: Information quality assessment methodology.

J C Worthington1, G Brilis

  • 1USEPA Office of Environmental Information, Washington, DC 20460, USA. worthington.jeffrey@epa.gov

Quality Assurance (San Diego, Calif.)
|May 15, 2002
PubMed
Summary
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This study introduces a quality assessment methodology to help information workers understand and improve data quality in their systems. Effective data quality management is crucial for enterprise decision-making and process improvement.

Area of Science:

  • Information Science
  • Computer Science
  • Management Science

Background:

  • Quality assurance in software and hardware supports data integrity in information systems.
  • Information workers often lack awareness of the data quality within their systems.
  • Understanding enterprise data quality is vital for effective management and process enhancement.

Purpose of the Study:

  • To present a methodology for assessing information data quality.
  • To guide information workers in planning and implementing data quality assessments.
  • To improve the understanding and management of information quality.

Main Methods:

  • Identifying key information quality indicators.
  • Developing standardized assessment procedures.

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  • Conducting systematic information quality assessments.
  • Reporting assessment findings.
  • Monitoring and tracking quality improvements over time.

    • Main Results:

    • Provides a structured approach to information quality assessment.
    • Enables identification of specific data quality issues.
    • Facilitates targeted improvements in data management processes.
    • Empowers information workers with actionable quality insights.

    Conclusions:

    • Implementing the proposed methodology enhances data quality awareness and management.
    • Systematic assessment leads to measurable improvements in information quality.
    • Effective information quality management supports better business decision-making and operational efficiency.