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Data & AI Training

Foundations of Data Quality

Defining what “good enough” means for data so decisions can be trusted and effort is focused where it matters.

Code: DQ1 Track: Data Quality Length: 1 hour (other formats available) Level: Foundation
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Overview

Data quality is often approached as a technical problem, measured in isolation from how data is actually used. This session reframes data quality as a business concept: data is only “good” if it is fit for its intended purpose.

Participants are introduced to the six core dimensions of data quality and how they relate to business outcomes, decision-making and risk. The focus is on building a shared understanding of quality expectations rather than creating abstract standards that nobody uses.

Who it is for

  • Executives and leaders relying on data for decisions.
  • Data Owners and Stewards accountable for data quality outcomes.
  • Analysts and operational teams working with critical data.
  • Governance and quality leads establishing quality foundations.

What you will learn

  • What data quality really means in a business context.
  • The six dimensions of data quality and how they apply in practice.
  • How “fit for purpose” differs across use cases.
  • Why chasing perfection wastes effort and slows delivery.
  • How data quality links to trust, risk and performance.
  • How quality underpins Gate 3: Assessment in the 8-Gate Framework.

Agenda

  • Why data quality initiatives fail.
  • Defining quality in business language.
  • The six dimensions of data quality.
  • Fit-for-purpose quality by use case.
  • Examples of good and bad quality definitions.
  • Discussion and Q&A.

Delivery and format

Delivered as a 1 hour interactive session. Can be extended into a working session to define quality expectations for priority data sets.

  • Format: Live virtual or on site.
  • Group size: Up to 25 participants recommended.
  • Optional: Follow-up roadmap working session with your leadership team.

Next steps

This course is commonly followed by: DQ2 · Data Quality Assessment & Profiling, DG6 · Issues Management and DG7 · Root Cause Analysis Together, these form a practical quality foundations pathway.