Preparing third-party input data - AWS Entity Resolution
Step 1: Subscribe to a provider service on AWS Data ExchangeStep 2: Prepare third-party data tablesStep 3: Save your input data table in a supported data formatStep 4: Upload your input data table to Amazon S3Step 5: Create an AWS Glue table

Preparing third-party input data

Third-party data services provide identifiers that can be matched with your known identifiers.

AWS Entity Resolution currently supports the following third-party data provider services:

Data provider services
Company Name Available AWS Regions Identifier
LiveRamp US East (N. Virginia) (us-east-1), US East (Ohio) (us-east-2), and US West (Oregon) (us-west-2) Ramp ID
TransUnion US East (N. Virginia) (us-east-1), US East (Ohio) (us-east-2), and US West (Oregon) (us-west-2) TransUnion Individual and Household IDs
Unified ID 2.0 US East (N. Virginia) (us-east-1), US East (Ohio) (us-east-2), and US West (Oregon) (us-west-2) raw UID 2

The following steps describe how to prepare third-party data to use a provider service-based matching workflow or a provider service-based ID mapping workflow.

Step 1: Subscribe to a provider service on AWS Data Exchange

If you have a subscription with a provider service through AWS Data Exchange, you can run a matching workflow with one of the following provider services to match your known identifiers with your preferred provider. Your data will be matched with a set of inputs defined by your preferred provider.

To subscribe to a provider service on AWS Data Exchange

  1. View the provider listing on AWS Data Exchange. The following provider listings are available:

  2. Complete one of the following steps, depending on your offer type.

    • Private offer – If you have an existing relationship with a provider, follow the Private products and offers procedure in the AWS Data Exchange User Guide to accept a private offer on AWS Data Exchange.

    • Bring your own subscription – If you already have an existing data subscription with a provider, follow the Bring Your Own Subscription (BYOS) offers procedure in the AWS Data Exchange User Guide to accept a BYOS offer on AWS Data Exchange.

  3. After you have subscribed to a provider service on AWS Data Exchange, you can then create a matching workflow or an ID mapping workflow with that provider service.

For more information about how to access a provider product that contains APIs, see Accessing an API product in the in the AWS Data Exchange User Guide.

Step 2: Prepare third-party data tables

Each third-party service has a different set of recommendations and guidelines to help ensure a successful matching workflow.

To prepare third-party data tables, consult the following table:

Data provider services guidelines
Provider service Unique ID needed? Actions
LiveRamp Yes

Ensure the following:

  • The Unique ID can be either your own pseudonymous identifier or a row ID.

  • Your data input file format and normalization is aligned with the LiveRamp guidelines.

    For more information about input file formatting guidelines for the matching workflow, see Perform Identity Resolution Through ADX in the LiveRamp documentation.

    For more information about input file formatting guidelines for the ID mapping workflow, see Perform Transcoding Through ADX in the LiveRamp documentation.

TransUnion Yes

Ensure the following:

  • A Unique ID exists for TransUnion Data Enrichment.

    Note

    Pass along attributes are allowed to persist in input and output to TransUnion. Household E keys and HHID are specific to the client namespace.

  • Phone number should be 10 digits, without any special characters such as spaces or hyphens.

  • Addresses should be split into

    • a single address line (combine address lines 1 & 2, if present)

    • city

    • zip (or zip plus4), without any special characters such as spaces or hyphens

    • state, specified as 2 letter code 3

  • Email addresses should be in plaintext.

  • First Name can be lower or upper case, nicknames are supported, but titles and suffixes should be excluded.

  • Last Name can be lower or upper case, middle initials to be excluded.

Unified ID 2.0 Yes

Ensure the following:

  • The Unique ID can't be a hash.

  • UID2 supports both email and phone number for UID2 generation. However, if both values are present in the schema mapping, the workflow duplicates each record in the output. One record uses the email for UID2 generation and the second record uses phone number. If your data includes a mix of emails and phone numbers and you don't want this duplication of records in the output, the best approach is to create a separate workflow for each, with separate schema mappings. In this scenario, go through the steps twice—create one workflow for emails and a separate one for phone numbers.

Note

A specific email or phone number, at any specific time, results in the same raw UID2 value, no matter who made the request.

Raw UID2s are created by adding salts from salt buckets which are rotated approximately once a year, causing the raw UID2 to also be rotated with it. Different salt buckets rotate at different times throughout the year. AWS Entity Resolution currently does not keep track of rotating salt buckets and raw UID2s, so it is recommended that you regenerate the raw UID2s daily. For more information, see How often should UID2s be refreshed for incremental updates? in the UID 2.0 documentation.

Step 3: Save your input data table in a supported data format

If you already saved your third-party input data in a supported data format, you can skip this step.

To use AWS Entity Resolution, the input data must be in a format that AWS Entity Resolution supports. AWS Entity Resolution supports the following data formats:

  • comma-separated value (CSV)

    Note

    LiveRamp only supports CSV files.

  • Parquet

Step 4: Upload your input data table to Amazon S3

If you already have your third-party data table in Amazon S3, you can skip this step.

Note

The input data must be stored in Amazon Simple Storage Service (Amazon S3) in the same AWS account and AWS Region in which you want to run the matching workflow.

To upload your input data table to Amazon S3

  1. Sign in to the AWS Management Console and open the Amazon S3 console at https://console.aws.amazon.com/s3/.

  2. Choose Buckets, and then choose a bucket to store your data table.

  3. Choose Upload, and then follow the prompts.

  4. Choose the Objects tab to view the prefix where your data is stored. Make a note of the name of the folder.

    You can select the folder to view the data table.

Step 5: Create an AWS Glue table

The input data in Amazon S3 must be cataloged in AWS Glue and represented as an AWS Glue table. For more information about how to create an AWS Glue table with Amazon S3 as the input, see Working with crawlers on the AWS Glue console in the AWS Glue Developer Guide.

Note

AWS Entity Resolution doesn't support partitioned tables.

In this step, you set up a crawler in AWS Glue that crawls all the files in your S3 bucket and create an AWS Glue table.

Note

AWS Entity Resolution doesn't currently support Amazon S3 locations registered with AWS Lake Formation.

To create an AWS Glue table

  1. Sign in to the AWS Management Console and open the AWS Glue console at https://console.aws.amazon.com/glue/.

  2. From the navigation bar, select Crawlers.

  3. Select your S3 bucket from the list, and then choose Add crawler.

  4. On the Add crawler page, enter a Crawler name and then choose Next.

  5. Continue through the Add crawler page, specifying the details.

  6. On the Choose an IAM role page, choose Choose an existing IAM role and then choose Next.

    You can also choose Create an IAM role or have your administrator create the IAM role if needed.

  7. For Create a schedule for this crawler, keep the Frequency default (Run on demand) and then choose Next.

  8. For Configure the crawler’s output, enter the AWS Glue database and then choose Next.

  9. Review all of the details, and then choose Finish.

  10. On the Crawlers page, select the check box next to your S3 bucket and then choose Run crawler.

  11. After the crawler is finished running, on the AWS Glue navigation bar, choose Databases, and then choose your database name.

  12. On the Database page, choose Tables in {your database name}.

    1. View the tables in the AWS Glue database.

    2. To view a table's schema, select a specific table.

    3. Make a note of the AWS Glue database name and AWS Glue table name.