Improve Accuracy of Insights at Scale Using Graph-Based Entity Resolution
Thursday, November 21
10:00am PT | 1:00pm ET
40 Minutes
Organizations rely on high-quality data insights for making decisions. Entity resolution is the process of linking and resolving data entities to help disentangle and consolidate your data. As a result, you not only boost the accuracy of insights from your data but also make your data more actionable for analytics and reporting.
However, the more voluminous and complex your data grows, the more difficult it becomes to scale your entity resolution solution, especially if you need to run multi-hop queries on large amounts of incomplete or inconsistent data.
Thankfully, graph databases offer more accuracy and flexibility for entity resolution.
Join us on November 21 for a 30-minute overview of:
- Key challenges with entity resolution
- How to match entities using linkages in graphs
- How the Neo4j database and data science algorithms are the ideal choice for addressing your entity resolution challenges
SPEAKER
John Stegeman
Product Specialist
John “Steggy” Stegeman is a Senior Graph Database Product Specialist with Neo4j. Prior to joining Neo4j, he held solution architect and consulting roles at Oracle, DXC, Waterline Data, and Hitachi Vantara. John is a self-avowed technology nerd who loves using technology to solve real-world enterprise challenges.
