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Improving Data Quality with Generative AI

Learn how generative AI can support data quality work through anomaly explanations, triage, and data contracts. This course will teach you how to validate LLM-assisted outputs against source data and checks.

Beginner
59m

Created by Nicolae Caprarescu

Last Updated Aug 14, 2026

Course Thumbnail
  • Course

Improving Data Quality with Generative AI

Learn how generative AI can support data quality work through anomaly explanations, triage, and data contracts. This course will teach you how to validate LLM-assisted outputs against source data and checks.

Beginner
59m

Created by Nicolae Caprarescu

Last Updated Aug 14, 2026

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What you'll learn

Generative AI can support data quality work, but data engineers need clear ways to decide where LLMs fit and how their outputs should be validated. In this course, Improving Data Quality with Generative AI, you’ll gain the ability to use LLMs for data quality workflows while keeping results grounded in source data, statistical checks, and contract validation. First, you’ll explore how LLM-assisted work compares with rule-based validation and established data quality checks. Next, you’ll discover how to use sample data to produce anomaly explanations, stakeholder-ready summaries, and severity triage. Finally, you’ll learn how to generate and maintain data contracts when upstream schemas change. When you’re finished with this course, you’ll have the skills and knowledge of generative AI for data quality needed to evaluate LLM-assisted findings, reduce hallucination risk, and protect downstream data work from unsupported outputs.

Improving Data Quality with Generative AI
Beginner
59m
Table of contents

About the author
Nicolae Caprarescu - Pluralsight course - Improving Data Quality with Generative AI
Nicolae Caprarescu
15 courses 3.4 author rating 265 ratings

Nicolae has been a Software Engineer since 2013, focusing on Java and web stacks. Nicolae holds a degree in Computer Science and enjoys teaching, traveling and motorsports.

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