Target Showcases Enhanced Retail Discovery and Reduced Database Maintenance with Spanner Graph
This article details how Target migrated its retail product discovery platform to Google Cloud Spanner Graph, consolidating fragmented data systems for search, vector, and transactional data. By building an enterprise ontology on Spanner Graph, Target enabled unified GraphRAG, semantic search, and transactional workloads, powering AI-driven conversational shopping assistants. The transition resulted in a 50% reduction in database maintenance overhead and enhanced recommendation relevancy for millions of shoppers, particularly during peak retail events. Target executed the critical infrastructure migration incrementally with zero downtime.
- →Addressing Fragmented Data for AI-Driven Discovery
- →Unifying Data with Spanner Graph for an Enterprise Ontology
- →Zero-Downtime Migration to Spanner Graph
- →Achieved Operational Efficiency and Enhanced AI Capabilities
Notes (4) ›
- Addressing Fragmented Data for AI-Driven Discovery
Target's previous retail discovery platform relied on fragmented Elasticsearch and NoSQL systems, leading to disconnected context, high operational overhead, and challenges in building AI-driven personalization.
- Unifying Data with Spanner Graph for an Enterprise Ontology
Target adopted Google Cloud Spanner Graph to consolidate semantic, graph, vector, and transactional data, creating a unified 'graph-of-graphs' enterprise ontology to support real-time personalization at global scale.
- Zero-Downtime Migration to Spanner Graph
The transition to Spanner Graph involved a four-phase, zero-downtime migration process, including schema mapping, parallel data integration, canary deployment, and a full cutover, ensuring continuous service for millions of guests.
- Achieved Operational Efficiency and Enhanced AI Capabilities
By leveraging Spanner Graph, Target reduced database maintenance by 50%, improved recommendation relevancy through a unified GraphRAG foundation, and gained serverless scalability for peak retail traffic.
https://cloud.google.com/blog/topics/retail/how-target-rebuilt-retail-discovery-with-spanner-graph/
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