What is Enterprise Data Integrity Testing (EDIT) and why is it important?

  • Enterprise data integrity testing is a process of ensuring that data across an entire organization is accurate, complete, and consistent. It involves testing data across multiple systems, databases, applications, and processes to identify any discrepancies, errors, or inconsistencies that could impact business operations, compliance, or decision-making.
  • Enterprise data integrity testing is important because organizations rely on accurate and reliable data to make informed decisions, comply with regulations, and deliver high-quality products and services. Without effective data integrity testing, organizations may be at risk of making decisions based on inaccurate or incomplete data, which can lead to financial loss, compliance issues, and damage to reputation.

Some key elements of enterprise data integrity testing include:

  • Scope: Enterprise data integrity testing should cover all relevant data across the organization, including data from multiple systems, databases, applications, and processes.
  • Automation: Due to the large scale of enterprise data, automation is essential for effective data integrity testing. Automated testing tools can help to identify data discrepancies, errors, or inconsistencies across multiple data sources and provide comprehensive reports.
  • Validation: Enterprise data integrity testing should include validation of data input and output processes, as well as verification of data storage and retrieval processes.
  • IntegrationEnterprise data integrity testing should integrate with existing testing processes and tools used by the organization.
  • Compliance: Enterprise data integrity testing should ensure that data complies with relevant regulations and standards.

Proactive’s Approach to EDIT:


  • Discovery and Assessment
    • Outputs:
  • Engagement Models used:
    • Workshop – Group/Organization – educate and joint assessment
    • Targeted – Specific Business Process – evaluate and assess
  • Design, Develop, Refine
    • Outputs:
  • Implement and Operate
    • Outputs: