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Case studyData engineering & the warehouse/lakehouseGoogle Cloud
Google Cloud — Data & AI · Read source ↗

Target is leveraging Spanner Graph to enhance retail discovery and reduce database maintenance by 50%. The focus is on understanding semantic meaning and relationships between products, categories, and guest intent, moving beyond simple keywords.

MyDataWork POV — Target's embrace of Spanner Graph to cut database maintenance by half sounds like a win, but there's a lurking concern. By focusing heavily on semantic relationships and guest intent, there's a risk of over-personalization. This could lead to a narrow shopping experience where customers are nudged into echo chambers of past preferences. Instead of broadening horizons, Target might inadvertently shrink them, limiting discovery to what algorithms deem relevant. The promise of personalization must be balanced with genuine exploration.
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