SPOTLIGHT PRESENTATION: LEVERAGING GRAPH DATABASES TO ENRICH CUSTOMER MASTER DATA & INSIGHTS

Graph databases are redefining how enterprises understand and manage relationships within their customer ecosystems. What was once siloed data across CRM, ERP, and IoT systems is now being connected into dynamic relationship graphs that reveal patterns, dependencies, and opportunities traditional databases can’t uncover.

As organizations strive to create a single source of truth for customer data, the challenge lies not just in integrating systems like Salesforce and Oracle - but in understanding how customers, locations, contracts, and transactions interconnect. The true differentiator lies in how enterprises architect, govern, and operationalize graph-based intelligence to improve data accuracy, decision-making, and customer experiences. Building an intelligent, connected customer master requires a balance of data engineering precision and business context awareness - designing models that can detect duplicates, correct address mismatches, and surface cross-sell opportunities while ensuring scalability, data quality, and trust.

Topics of discussion will include, but not be limited to:

• Designing graph-based data models that unify customer entities across systems
• Detecting duplicates, incomplete records, and mismatched addresses using graph analytics
• Integrating graph insights with AI, data quality, and CRM governance frameworks
• Measuring business impact through improved accuracy, customer satisfaction, and operational efficiency
• Scaling graph architectures for enterprise adoption, data trust, and continuous improvement

Phani Chilakapati, Global Data Architecture Leader, Digital Transformation, GenAI & Enterprise Analytics, INDUSTRIAL SCIENTIFIC