Automated Big Data Quality Assessment using Knowledge Graph Embeddings

📰 ArXiv cs.AI

Learn to automate big data quality assessment using knowledge graph embeddings for accurate context-aware evaluation

advanced Published 20 May 2026

Action Steps

Build a knowledge graph representing data quality rules and dimensions
Utilize knowledge graph embeddings to predict missing edges between input dataset context and quality rules
Configure the embedding model to learn from the knowledge graph structure
Test the approach on a sample dataset to evaluate its accuracy
Apply the automated data quality assessment to large-scale big data projects

Who Needs to Know This

Data scientists and data engineers can benefit from this approach to improve data quality assessment in big data projects, ensuring accurate and reliable insights

Key Insight

💡 Knowledge graph embeddings can enhance automated data quality assessment by providing context-aware evaluation

Key Takeaways

Learn to automate big data quality assessment using knowledge graph embeddings for accurate context-aware evaluation

Full Article

Title: Automated Big Data Quality Assessment using Knowledge Graph Embeddings

Abstract:
arXiv:2605.18833v1 Announce Type: cross Abstract: Automated data quality assessment is crucial for managing big data, but existing solutions face challenges in achieving accurate context-aware assessment. This paper presents a novel knowledge-based approach to enhance automated data quality assessment. Our approach utilizes knowledge graph embeddings to predict missing edges between the input dataset's context representation and the relevant quality rules and dimensions within a knowledge graph

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