The document discusses Bloom and Graph Data Science (GDS) tools for visualizing graph insights. Bloom is introduced as a graph visualization tool that is no-code/low-code and can handle thousands of nodes. GDS is described as including graph algorithms like centrality measures and community detection. An example problem of finding the most important London Underground station is presented, and it is noted that the answer depends on how importance is defined. Bloom and GDS are suggested for finding the answer by analyzing the graph.

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Visualising Insights With Bloom
and Graph Data Science
Yi Ren Sum
Software Engineer, Neo4j Bloom

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Introduction to Bloom and GDS

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Bloom
• Graph-visualisation tool
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Bloom
• Graph-visualisation tool
• No-code, low-code
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Bloom
• Graph-visualisation tool
• No-code, low-code
• Thousands of nodes
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Graph Data Science (GDS)
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Graph Algorithms
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• Centrality
• Degree Centrality
• Betweenness Centrality
• Community-detection
• Louvain
• Weakly Connected Components
• …

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A Story

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Which is the most important station in London?
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It depends…
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It depends…on what you define as ‘important’
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Find the answer, using Bloom and GDS
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Released in v2.3.0 of Bloom
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Thank you!
Connect:
yi-ren.sum@neo4j.com
https://linkedin.com/in/sumyiren/

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Some screenshots
Connect:
yi-ren.sum@neo4j.com
https://linkedin.com/in/sumyiren/

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Degree Centrality
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Betweeness
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Louvain Bus Map
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Louvain Bus Map
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