• views: 166
• date: 19 August 2026
• posted by: voska89

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.
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.

Homepage

https://app.pluralsight.com/ilx/video-courses/improving-data-quality-generative-ai/course-overview

   
   
   

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