Graph Database Applications and Architectures in DataFun Knowledge Map 3.0
The DataFun Knowledge Map 3.0’s graph database module, presented by Ant Group expert Cui Anqi, outlines how graph databases enhance complex analysis through risk‑control architectures, user‑relationship recommendation, data‑governance, a new graph‑based data management system, and the GraphRAG framework, while also offering a free download link.
In the DataFun Data Intelligence Knowledge Map 3.0, the graph database module, presented by Ant Group expert Cui Anqi, explains how graph databases improve complex analysis efficiency.
Ant Group’s full‑graph risk control architecture
User relationship propagation and search recommendation built on graph databases
Data governance and privacy data identification using graph databases
The new graph‑based data management system
GraphRAG (graph‑enhanced retrieval‑augmented generation) architecture and related topics
Cui Anqi, a senior solution architect in Ant Group’s graph computing team, holds a PhD from Tsinghua University and has authored books on big‑data intelligence, natural‑language processing, and machine learning.
DataFun Knowledge Map 3.0 involves 47 experts, over 2,500 knowledge points, and covers the entire data lifecycle—from data collection, lake and warehouse, governance, A/B testing, graph databases, large‑model fine‑tuning, RAG, agents, risk control, recommendation, to emerging topics such as data weaving, ChatBI, AI search, and AI infrastructure.
Readers are invited to join the group to download Knowledge Map 3.0 for free.
DataFunSummit
Official account of the DataFun community, dedicated to sharing big data and AI industry summit news and speaker talks, with regular downloadable resource packs.
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