Empowering Identity Resolution with Vector Databases
Year: 2025
Type: article
Abstract: In today's data-driven landscape, effective Identity Resolution (IDR) has become essential for businesses seeking to consolidate and manage vast and diverse datasets. Traditional identity resolution methods often struggle to handle the growing complexity, volume, and dimensionality of modern data. Vector databases, designed to manage and query high-dimensional data, present a powerful solution to these challenges. By leveraging vector-based representations, businesses can achieve more accurate, faster, and scalable identity resolution. This paper examines the advantages of using vector databases in IDR, highlighting how they outperform traditional databases in handling complex data relationships. Additionally, it explores how vector databases enhance various modern machine learning applications, such as semantic search, ultimately providing businesses with a more efficient and effective means of resolving identities and optimizing customer insights.
DOI: 10.55041/ijsrem41864
Author: Arpit Jain
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4407971929