Using Data and AI to Democratize Entity Resolution and Master Data Management
By Ben Lorica, Host of the Data Exchange Podcast
The Data Exchange is an independent podcast series focused on data, machine learning and AI. Learn why Senzing CEO, Jeff Jonas, thinks entity resolution is deceptively complex – and a challenge to tackle on your own.
Jeff explains that while entity resolution may seem straightforward at first, requirements like accuracy, scale, latency, real-time updates, and privacy make it a deceptively complex problem with many applications. These include customer data management, fraud detection, data quality enhancement, data integration, data governance, and business intelligence.
The devil is in the details when it comes to entity resolution, making it an intriguing yet formidable challenge to tackle on your own. Jeff describes interesting concepts such as sequence neutrality and principle-based entity resolution, and he explains the role emerging technologies (such as LLMs, vector databases & vector search, graph databases) might play in large-scale, real-time entity resolution systems using data and AI to democratize entity resolution and master data management.