Welcome to This Week in Neo4j, your weekly fix for news from the world of graph databases!
This week was challenging to find something not about LLMs, Vectors and the like, but you can find a video on Metadata Management and findings from building a finance app with Streamlit and Neo4j.
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COMING UP NEXT WEEK!
- NODES 2023: Watch Recordings
- Live Stream: Neo4j Live: CypherGUI – user friendly administration for Neo4j on February 13
- Meetup: Meet us in Brisbane, AUS on February 13
- All Neo4j Events: Webinars and More
- GraphSummit Series: Get Connected With Graphs – New Dates for 2024 now live!
FEATURED NODES SPEAKER: Dattaraj Rao
Dattaraj leads the AI Research Lab at Persistent and drives thought leadership in AI/ML across the company. The team explores state-of-the-art algorithms in Computer Vision, Natural Language Understanding, Probabilistic Programming and more.
Connect with him on LinkedIn.
In his session at NODES “NeoGenAI: Ontology Guided Loading of Business Data in Graph Database” Dattaraj demonstrates a systematic approach to populating a knowledge graph based on a standard ontology (like FIBO, insurance risk) enabling you to build a knowledge graph guided by ontology in a standardised manner.
VECTOR DATABASE: Tutorial: Semantic Search, RAG and Index Vector DatabasesIn her tutorial, Erica Brown compares Vector Databases and Graph Databases for RAG, to learn more about the technology and its implementation.
METADATA MANAGEMENT: Anansi – Visual Metadata Management ToolData integrity increasingly becomes a challenge due to the surge in volume within data-driven enterprises. Anansi is a Visual Data Lineage Tool to simplify data webs and ensure effective decision-making, quality assurance, and compliance.
INTEGRATION: Streamlit + Neo4j Integration for Financial InsightsVaibhav Koneti launched a project merging Streamlit’s interactive UI and Neo4j’s graph database capabilities into a dynamic Income and Expense Tracker. He takes us on his development journey for advanced financial insights.
TWEET OF THE WEEK: Haystack
Hold on to your nodes, graph database fans. The @neo4j Haystack integration just dropped.— Haystack (@Haystack_AI) January 30, 2024
This integration comes with a document store that relies on Vector search indexes and two retrievers. One to query documents using vector embeddings, and another one that can be used to… pic.twitter.com/1Z1J2TrMZS
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