Our customer, a premier, global research organization, produces large quantities of intellectual property in the form of whitepapers, webinars, and articles. They also provide high-value, analyst-based, advisory services to organizations requiring a combination of business and information technology insights. The customer wanted the ability to exercise more fine-grained authorization control and faster content access, both to ensure a positive customer experience and reduce potential revenue leakage.
The customer required a solution to manage the ever-expanding number of relationships among the forms of content produced and their growing customer base with fine-grained content access requirements. A fast and efficient means of determining which users and organizations were authorized to access what content was required. Managing relationships between content and user authorization at run time is complex and if not done well will be the source of a poor user experience. Worse, it can be the source of the revenue leakage attempting to be addressed in the form of unpaid access to content and services.
Skylytics architected a solution that combed microservices, data streaming, and a Neo4j Graph database to deliver a reliable, performant, and scalable solution to solve this challenge. Customer Authorization, content metadata, detail, and Taxonomy are streamed in real-time from multiple upstream sources, the graph is kept in sync with the upstream systems to allow for successful management of the complex relationship that exists between users and content.
The Neo4j database enabled the implementation of a comprehensive Knowledge Graph to model the content, users, and authorization. Knowledge Graphs have emerged as a powerful tool for businesses to remain competitive in rapidly evolving industries. Organizing data using knowledge graphs allows users to efficiently answer complex questions and gain insights from interconnected data sources where traditional relational databases fall short.
The Neo4j Knowledge Graph provides the customer with additional benefits as well. The Graph enabled them to move away from hardcoded access rules and towards a more modular and flexible approach using Cypher queries. A reduction in the number of connections between services previously needed to complete the authorization task was also achieved. They can now also answer questions that were previously difficult or near impossible to answer with traditional relational databases due to the number of many-to-many relationships that exist.
Neo4j has also helped facilitate Graph Data Science using embedded features in Neo4j and as well as enhancing their Business In. The company is now able to address potential customer churn, potential revenue leakage, basket analysis, and clustering to expose actual customer segmentation. These capabilities enable their business to proactively address customer concerns, ethically target new business, minimize potential revenue loss, and deliver a more seamless user experience.
Knowledge graphs have demonstrated their potential to revolutionize traditional data management practices and optimize business operations, particularly in ecosystems with multiple data silos and complex relationships. The implementation of a knowledge graph fosters a more data-driven culture and enhances the capabilities of Business Intelligence while delivering valuable benefits such as better customer retention, maximized revenue opportunities, and improved user access to relevant information.