Udemy

Free Data Quality Course: Understand Data Problems and Plan Lasting Improvements

Kieran Keene looks at data quality as a combination of records, processes and ownership. The opening lessons introduce quality dimensions, then ask what data an organization holds, where it moves and how profiling can reveal missing values, duplicates or inconsistent patterns.

Free Data Quality Course: Understand Data Problems and Plan Lasting Improvements — Kieran Keene. WikiFree selection.
Free learning access

Listed as Free on Udemy when checked on 22 October 2026. No coupon or subscription trial is required for the listed lessons. Enrollment needs a Udemy account; availability can change.

About this course

Kieran Keene looks at data quality as a combination of records, processes and ownership. The opening lessons introduce quality dimensions, then ask what data an organization holds, where it moves and how profiling can reveal missing values, duplicates or inconsistent patterns.

Resolution is considered at three levels: technical pipelines, business processes and organizational behaviour. The final planning lesson brings those strands together, making the course useful for someone who needs to discuss a data-quality initiative across technical and business teams.

Official course Data Quality Essentials: A Crash Course
Created by Kieran Keene
Platform Udemy
Language English
Level Beginner — Udemy listing
Listed duration 60 minutes; 11 lectures across 4 sections
Certificate Not included with a new free enrollment

Skills you’ll gain

  • Recognizing common dimensions of data quality
  • Using profiling and analysis to investigate data issues
  • Distinguishing technical fixes from process and ownership changes
  • Organizing a plan to improve and monitor data reliability

The listing contains eleven lectures over one hour and requires no prior experience. The creator explicitly describes the course as a grounding in the subject rather than expert-level training. A short tools entry and a quiz are included, but a substantial coding lab or production pipeline build is not documented.

No particular commercial data platform is required to understand the lessons. Independent practice can begin with a small non-sensitive spreadsheet and simple checks, while enterprise tools discussed later may have separate costs. The course’s contribution is the combined planning perspective, not a claim that software alone will repair every data-quality issue.

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Choose your next step

Focus on reference data: Reference-data quality and management. Explore a specific category of information that affects consistency across systems.

Understand shared business records: Master data management and trusted records. Develop the ownership and consistency side of the improvement plan.

Frequently asked questions

Will this teach me to build a production data pipeline?

Pipelines are discussed as one part of quality improvement. The public syllabus does not establish a complete production implementation project.

Is the subject only technical?

No. Business processes, people, ownership and cultural changes each receive explicit attention in the course.

Checked on 22 October 2026 using the public course details and syllabus. WikiFree has not watched every lesson or tested full playback. New free enrollments do not include a Udemy completion certificate, instructor Q&A or direct messages.

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