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YouTube

GraphBI: Expanding Analytics to All Data Through the Combination of GenAI, Graph, and Visual Analytics

MLOps.community via YouTube

Overview

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Explore how GraphBI combines GenAI, graph technology, and visual analytics to unlock the full potential of enterprise data in this 73-minute podcast episode from MLOps.community featuring Paco Nathan (Principal DevRel Engineer at Senzing) and Weidong Yang (CEO of Kineviz). Learn how traditional BI solutions only utilize about 20% of available information (structured data), while GraphBI aims to incorporate the remaining 80% of unstructured data. Unlike black-box RAG systems, GraphBI uses GenAI for transparent data pre-processing, converting unstructured information into graph-based formats that enable reliable, step-by-step analytics. The discussion covers the complete GraphBI workflow, from managing diverse data types to pre-processing with GenAI, iterative analytics using graph grammar, and effective insight presentation. Topics include PII anonymization techniques, differences between Graph RAG approaches, ontologies versus embeddings, data visualization strategies, access control considerations, and practical use cases across various domains including IoT.

Syllabus

[00:00] Wei's preferred coffee
[00:26] Takeaways
[00:50] Please like, share, leave a review, and subscribe to our MLOps channels! You can give us up to 5 stars on Spotify and leave your reviews!
[01:06] PII Anonymization Techniques
[09:49] Graph RAG Differentiation Ideas
[19:55] Ontologies vs Embeddings in AI
[30:05] Graph Exploration and Insight
[39:25] Iceberg Data Metaphor
[41:19] Contextual Data Visualization
[42:44] Granularity vs Domain Shifting
[49:51] Visualization Access Control
[53:37] Graph RAG Use Cases
[59:16] IoT and Graphs
[1:01:15] Data Visualization
[1:12:14] Wrap up

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MLOps.community

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