AWS Entity Resolution
#181 · Level 3 · Modern architecture · Data and analyticsConcept
Section titled “Concept”AWS Entity Resolution matches records from different places to find which ones are actually the same person or organization. The matching runs in a matching workflow. The matching method can be your own rules, machine learning, or a service from an outside data provider. First, a schema mapping tells it which columns hold the name, address or phone number. Records that match get a common ID, and the results are written to S3.
Simple example
Section titled “Simple example”“Md. Rahim”, “Mohammad Rahim”, “Rahim M.” — written under three names in three ledgers, but actually the same person; finding that out.
Why it’s needed
Section titled “Why it’s needed”If the same customer appears in different systems with different spellings, you can’t get a full picture of them.
Where it’s used
Section titled “Where it’s used”Unifying customer data, finding duplicate records.
Azure equivalent
Section titled “Azure equivalent”No direct match; closest: Microsoft Dynamics 365 Customer Insights
Learn more
Section titled “Learn more”For details and the latest information, see the official documentation: