AWS entityresolution documentation change
Summary
Restructured documentation about matching workflows, added sections for workflow types, data output options, and results. Clarified compatibility between matching types and output destinations.
Security assessment
The changes primarily reorganize content and clarify feature capabilities. While there's a mention of data hashing for control, this was already present in the original text and is not a new security feature. No concrete evidence of addressing a security vulnerability or weakness.
Diff
diff --git a/entityresolution/latest/userguide/create-matching-workflow.md b/entityresolution/latest/userguide/create-matching-workflow.md index 0e74ce8aa..217a58e60 100644 --- a//entityresolution/latest/userguide/create-matching-workflow.md +++ b//entityresolution/latest/userguide/create-matching-workflow.md @@ -5,3 +5 @@ -# Match input data using a matching workflow - -A _matching workflow_ is a data processing job that combines and compares data from different input sources and determines which of it matches based on different matching techniques. It produces a data output table. +Matching workflow types Data output options Matching workflow results @@ -9,3 +7 @@ A _matching workflow_ is a data processing job that combines and compares data f -When you create a matching workflow, you first specify your data inputs, normalization steps, and then choose your desired matching techniques and data output. AWS Entity Resolution reads your data from your specified location or locations and finds a match between two or more records in your data. It then assigns a [Match ID](./glossary.html#match-id-defin) to the records in the matched set of data. AWS Entity Resolution then writes data output files to a location that you choose. You can use AWS Entity Resolution to hash output data if desired – helping you maintain control over your data. - -A matching workflow can have multiple runs and the results (successes or errors) are written to a folder with the `jobId` as the name. +# Match input data using a matching workflow @@ -13 +9 @@ A matching workflow can have multiple runs and the results (successes or errors) -The data output contains both a file for successful matches and a file for errors. The data output can contain multiple fields. The successful results are written to a `success` folder that contains multiple files, and each file contains a subset of the successful records. Similarly, errors are written to an `error` folder with multiple fields, with each containing a subset of the error records. For more information about troubleshooting errors, see [Troubleshooting matching workflows](./troubleshooting.html). +A _matching workflow_ is a data processing job that combines and compares data from different input sources and determines which records match based on different matching techniques. AWS Entity Resolution reads your data from your specified locations, finds matches between records, and assigns a [Match ID](./glossary.html#match-id-defin) to each matched set of data. @@ -19,10 +15 @@ The following diagram summarizes how to create a matching workflow. -Before you create a matching workflow, you must first create a schema mapping. For more information, see [Creating a schema mapping](./create-schema-mapping.html). - -There are three ways to create a matching workflow, based on matching techniques: [rule-based](./creating-matching-workflow-rule-based.html), [machine learning-based](./create-matching-workflow-ml.html), or [provider service-based](./create-matching-workflow-provider.html). - -After you create and run a matching workflow, you can do the following: - - * View the results in the S3 location you specified. Matching workflows generate IDs after the data is indexed. - - * Use the output of [rule-based matching](./creating-matching-workflow-rule-based.html) or [machine learning (ML) matching](./create-matching-workflow-ml.html) as an input to [provider service-based matching](./create-matching-workflow-provider.html) or the other way around to meet your business needs. - +###### Topics @@ -29,0 +17 @@ After you create and run a matching workflow, you can do the following: + * Matching workflow types @@ -30,0 +19 @@ After you create and run a matching workflow, you can do the following: + * Data output options @@ -32,3 +21 @@ After you create and run a matching workflow, you can do the following: -For example, to save provider subscription costs, you can first run [rule-based matching](./creating-matching-workflow-rule-based.html) to find matches on your data. Then, you can send a subset of unmatched records to [provider service-based matching](./create-matching-workflow-provider.html). - -###### Topics + * Matching workflow results @@ -56,0 +44,78 @@ For example, to save provider subscription costs, you can first run [rule-based +## Matching workflow types + +AWS Entity Resolution supports three types of matching workflows: + +Rule-based matching + + +Uses configurable rules to identify matching records based on exact or fuzzy matching of specified fields. You define the matching criteria, such as matching names that are spelled similarly or addresses that are formatted differently. + +Machine learning-based matching + + +Uses machine learning models to identify similar records, even when the data has variations, errors, or missing fields. This approach can detect more complex matches than rule-based matching. + +Provider service-based matching + + +Uses third-party data providers to enrich and validate your data before matching. This type of matching is not compatible with Amazon Connect Customer Profiles output. + +## Data output options + +AWS Entity Resolution can write data output files to: + + * An Amazon S3 location that you specify + + * Amazon Connect Customer Profiles (for customer data deduplication) + + + + +###### Important + +Exporting to Amazon Connect Customer Profiles is not compatible with provider-based matching. To export to Amazon Connect Customer Profiles, you must use rule-based matching or machine learning-based matching. + +You can use AWS Entity Resolution to hash output data if desired – helping you maintain control over your data. + +The following table shows the three types of matching workflows and their supported output destinations. + +Matching type | S3 output | Customer Profiles Output +---|---|--- +[rule-based](./creating-matching-workflow-rule-based.html) | Yes | Yes +[machine learning-based](./create-matching-workflow-ml.html) | Yes | Yes +[provider service-based](./create-matching-workflow-provider.html) | Yes | No + +## Matching workflow results + +After you create and run a matching workflow, you can view the results in your specified S3 location or in Amazon Connect Customer Profiles. Matching workflows generate IDs after the data is indexed. + +A matching workflow can have multiple runs and the results (successes or errors) are written to a folder with the `jobId` as the name. + +For each run for S3 output destinations: + + * The data output contains both a file for successful matches and a file for errors + + * Successful results are written to a `success` folder containing multiple files + + * Errors are written to an `error` folder with multiple fields + + + + +For each run for Amazon Connect Customer Profiles output destinations: + + * Deduplicated customer records are sent directly to your Amazon Connect instance + + * You can view your recent job history in the AWS Entity Resolution console + + * Existing profiles in Amazon Connect are not included in the deduplication process + + + + +After you create and run a matching workflow, you can use the output of [rule-based matching](./creating-matching-workflow-rule-based.html) or [machine learning (ML) matching](./create-matching-workflow-ml.html) as an input to [provider service-based matching](./create-matching-workflow-provider.html) or the other way around to meet your business needs. + +For example, to save provider subscription costs, you can first run [rule-based matching](./creating-matching-workflow-rule-based.html) to find matches on your data. Then, you can send a subset of unmatched records to [provider service-based matching](./create-matching-workflow-provider.html). Note that if you plan to export to Customer Profiles, you should use rule-based or machine learning-based matching only. + +For more information about troubleshooting errors, see [Troubleshooting matching workflows](./troubleshooting.html). +