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
- Data Provider Matching: Enrich and match records with licensed data service provider datasets
- Privacy Integration: Encryption, hashing, and combination with AWS Clean Rooms for privacy-safe entity resolution across organizations
- Scalability: Processing via AWS Glue tables with manual bulk and automatic incremental processing
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, ML-based, and provider-based matching for high accuracy
- Minimized data movement through processing directly from S3/Glue
- Scalable for large data volumes via AWS Glue tables
- 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
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 reads input data via AWS Glue tables based on data in Amazon S3 (up to 20 data inputs per workflow). Input data is configured as schema mappings that define which fields are used for the matching process.
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