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Study mode:
on
1
Intro
2
Outline
3
Motivations
4
Starting points
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RDBMS and relationships: limitations
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Graph database model
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GraphDB: objectives
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GraphDB : less code
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Neo4j request
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How it works
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Limosa: detachment declaration
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DDT: sub-contractors
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Full schema
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Full query
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Implementation
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In SQL/RDBMS ?
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Data quality problem
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Addresses
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Duplicates combinations
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Schema with B duplicated
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Conclusions
22
References : www.smalsresearch.be
Description:
Explore graph databases for fraud detection in this 42-minute conference talk from Devoxx. Learn how graph databases excel at representing complex relationships between entities, outperforming traditional SQL databases in both response time and query writing. Discover the basic concepts of graph databases and gain insights from real-world experience in fraud detection within the Belgian social security sector. Understand the advantages of graph databases in various domains, including recommendation systems, social networks, and master data management. Follow along as the speaker introduces graph database models, demonstrates Neo4j requests, and compares implementation approaches with SQL/RDBMS. Examine practical examples such as Limosa detachment declarations and sub-contractor relationships, while also addressing data quality challenges like duplicate entries and address matching.

Fighting Fraud with Graph Databases

Devoxx
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