Skip to main content
Cloud / AWS / Products / AWS Entity Resolution - Record Matching and Linking

AWS Entity Resolution - Record Matching and Linking

AWS Entity Resolution is a service for matching and linking records across different data sources.

Analytics
Pricing Model Pay per record processed
Availability Selected regions
Data Sovereignty EU regions available
Reliability 99.9% availability SLA

What is AWS Entity Resolution?

AWS Entity Resolution is a service that helps organizations identify and link related records across different data sources. In many organizations, customer data, product data, or transaction data exists in different systems with varying formats, spellings, and identifiers. Entity Resolution brings this data together.

The service combines rule-based and ML-powered matching techniques to make reliable matches even with typos, different date formats, or incomplete address data. Source data remains in its respective storage locations: Entity Resolution does not move data but creates mapping tables.

The service is particularly valuable for creating 360-degree customer views, where customer data from CRM, e-commerce, support, and marketing systems is unified into a single customer profile.

Core Features

  • Rule-Based Matching: Configurable comparison rules for exact and fuzzy matches
  • ML-Based Matching: Automatic detection of related records even with erroneous or incomplete data
  • Schema Mapping: Define which fields from different sources are used for comparison
  • Privacy Integration: Combination with AWS Clean Rooms for privacy-safe entity resolution across organizations
  • Scalability: Processing millions to billions of records

Typical Use Cases

Customer Data Unification: Organizations merge customer data from CRM, e-commerce, and marketing systems into unified customer profiles. Entity Resolution also detects duplicates with different spellings or addresses.

Data Cleansing and Deduplication: Data teams use Entity Resolution to identify and clean duplicates in large datasets before loading data into a data warehouse or data lake.

360-Degree Customer View: Marketing and sales teams gain a complete picture of each customer by unifying all customer touchpoints, enabling personalized outreach and better service.

Benefits

  • Combination of rule-based and ML-based matching for high accuracy
  • No data movement: data stays in its source systems
  • Scales from thousands to billions of records
  • Integration with the AWS analytics ecosystem

Integration with innFactory

As an AWS Reseller, innFactory supports you with AWS Entity Resolution: from analyzing data sources and defining matching rules to integrating into existing data pipelines and quality assurance of matching results.

Typical Use Cases

Customer data unification
Data cleansing and deduplication
360-degree customer view

Frequently Asked Questions

What is AWS Entity Resolution?

AWS Entity Resolution is a service that uses ML-powered matching and rule-based techniques to identify and link related records across different data sources without requiring data to be shared.

How does the matching work?

The service offers rule-based matching with configurable comparison rules as well as ML-based matching that automatically detects matches even with typos, format differences, and incomplete data.

What data sources are supported?

AWS Entity Resolution works with data from AWS Glue, Amazon S3, and Amazon Redshift. Input data is configured as schema mappings that define which fields are used for the matching process.

AWS Cloud Expertise

innFactory is an AWS Reseller with certified cloud architects. We provide consulting, implementation, and managed services for AWS.

Ready to start with AWS Entity Resolution - Record Matching and Linking?

Our certified AWS experts help you with architecture, integration, and optimization.

Schedule Consultation