Data Quality Insights
Discover the four essential components that define data quality: metrics, metadata, lineage, and logs. These elements help identify potential issues within data streams, ensuring high fidelity and reliability. By understanding internal characteristics and external interactions, you can better reconstruct and assess the integrity of your data systems.In this clip
From this podcast

Super Data Science: ML & AI Podcast with Jon Krohn
SDS 541: Data Observability — with Dr. Kevin Hu
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