What Graph can do for Retail and Healthcare, Beyond Recommendations
Blog post from TigerGraph
Graph analytics offers transformative insights for retail and healthcare sectors by highlighting the interconnected relationships within their ecosystems, moving beyond traditional recommendation engines. In retail, graph analytics enhances fraud detection, demand forecasting, and supply chain visibility by mapping the intricate web of customer interactions, product dependencies, and transaction patterns, revealing underlying structures that are not apparent through isolated data analysis. Similarly, in healthcare, graph analytics exposes referral bottlenecks, coordination gaps, and medication interaction risks by analyzing the complex networks of patients, providers, and treatments, providing a comprehensive view that informs better decision-making and risk management. By storing and analyzing these connections directly, organizations can ask more nuanced questions about the behavior and movement of risk and influence across their systems, thereby gaining a strategic advantage through improved structural awareness and operational efficiency.
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