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Data Quality metrics and KPIs

What are Data Quality metrics?

Identifying the optimal Data Quality metrics can be challenging, especially when everyday tasks consume your time. To help you, we've assembled a list of examples to ignite your creativity.

Copy these examples into your preferred app, or you can also use Tability to keep yourself accountable.

Find Data Quality metrics with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.

Examples of Data Quality metrics and KPIs

Metrics for Data governance effectiveness

  • 1. Data quality score

    Represents the accuracy, completeness, and reliability of data. Calculated by evaluating data against predefined quality criteria.

    What good looks like for this metric: 95% or higher

    Ideas to improve this metric
    • Implement data validation rules
    • Conduct regular data quality audits
    • Utilise data cleansing tools
    • Ensure consistent data entry procedures
    • Provide regular training for data handlers

  • 2. Compliance rate

    Measures the percentage of data processes in compliance with relevant regulations and policies.

    What good looks like for this metric: 98% or higher

    Ideas to improve this metric
    • Establish clear data governance policies
    • Regularly review and update compliance guidelines
    • Implement automated compliance monitoring tools
    • Conduct periodic compliance training
    • Schedule regular internal audits

  • 3. Data breach incidents

    Tracks the number of data breaches or security incidents within a specified period.

    What good looks like for this metric: Zero breaches

    Ideas to improve this metric
    • Strengthen data security protocols
    • Conduct regular vulnerability assessments
    • Use encryption for sensitive data
    • Implement multi-factor authentication
    • Train employees on security best practices

  • 4. Data access control

    Measures the effectiveness of access controls by tracking unauthorised access attempts.

    What good looks like for this metric: Less than 2% unauthorised attempts

    Ideas to improve this metric
    • Regularly review and update access control policies
    • Implement role-based access control
    • Monitor and log access attempts
    • Conduct regular access audits
    • Use secure authentication methods

  • 5. Data retention adherence

    Assesses how closely data retention practices align with data governance policies.

    What good looks like for this metric: 100% adherence

    Ideas to improve this metric
    • Develop and communicate clear data retention policies
    • Implement automated data retention tools
    • Regularly review data retention schedules
    • Conduct training on data retention practices
    • Monitor and enforce compliance with retention policies
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Implement these metrics

Tracking your Data Quality metrics

Having a plan is one thing, sticking to it is another.

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

Tability Insights DashboardTability's check-ins will save you hours and increase transparency

More metrics recently published

We have more examples to help you below.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

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