As part of the normalization process, the InfoSum Platform lets you map US postal addresses in a source data file to the USA Address key in the Global Schema. Mapping US postal addresses to the Global Schema has a number of advantages:

• Three keys will be automatically generated after normalization (USA address, Zip9 and Zip5).
• US addresses can be entered in various formats.
• If you'd like to create custom name and address keys, you will need to import both first name and last name in separate columns
   

Note: US address mapping is only available for US East Cloud Vaults and Bunker Datasets.

Table of contents

Supported formats

Using the address mapper

Video tutorial

Creating custom name and address keys

Normalizing for Activation

Next steps

Supported formats

InfoSum verifies that the US address is valid and complete. You must always provide US addresses in raw format. 

The following Zip formats are supported by InfoSum Platform:

• Zip9 is accepted in two formats: 01740-1329 or 017401329
• Street address is required along with Zip code. The Platform cannot map or normalize Zip code on its own without a street. Both Street name and Zip code are required to validate an address.
• City and State are not mandatory values, unless zip code is not present.
• If an address has a Zip5, InfoSum Platform creates a Zip9 key.

Using the address mapper 

Video tutorial

Prior to normalizing your data you must have imported a file to your Cloud Vault. You can do this via the Import flow. Once you complete your import you’ll have to create a recordset before being able to normalize your data. 

For general information about the normalization step please read our Data Normalization article. You will need to be in the main Normalization screen to use the address mapper

1. To use Address Mapper, click on the black + icon on the right hand side, and select Address Mapper.

2.  This will open a modal where you can match column in your dataset to address mapper fields. 
3. Please ensure that you have selected the Address mapper Region on the dropdown as United States of America. Then you will see the following fields in green:
   1. House Number
   2. Address line 1/Full Address (you can include the street address and house number here)
   3. Address line 2
   4. Address line 3
   5. City
   6. State
   7. ZIP

4. Click on your columns (blue) to select a column if the address mapper hasn’t automatically selected the right column
5. Once you’re happy with the mapping, click on Add Address Mapper
6. You will see the address has been mapped in green and USA Address, Zip5 and Zip9 have been created as keys (the key toggle is automatically on). Do not change the name of these column. Keeping the name as is will maximize compatibility with other match partners using USA Address or Zip5 and Zip9

Creating custom name and address keys

You can easily create custom compound keys using the modification options.

The two keys listed below are recommended to be included in the Normalization config for all US customers with Name + Address in their Datasets:

• Full Name:USA Address
• Last Name:USA Address

Note: If you would like to use any keys other than those suggested above, please contact your InfoSum rep to ensure that the keys will be compatible with your match partner, as including these keys will override the recommended keys above. For specialized use case Datasets that require them, the other available Global Schema keys for name + address combinations include:

• FirstName::Address
• LastName::Zip9
• LastName::Zip5

You will need to follow the instructions below once per key:

1. Click on the black + button, select add modified column and select ‘Combine Keys’ 

2. Add input columns: these can be standard columns (like your name columns) or address mapper column (like the USA address key)
   
3. Input the settings of your custom keys as described below. You will need to do this once per key:
   • Full Name:USA Address*
     • Input column order: First Name, Last Name, USA Address
     • Global Schema Category “FullName::Address”
   • Last Name:USA Address*
     • Input column order: Last Name, USA Address
     • Global Schema Category “LastName::Address”
4. Click on add modified column.
   

4. Your new column will be added to the normalization table. It will be at the top in purple.
5. Mark all of the columns above as Keys by toggling the key column on (blue). 
6. Before finalizing, double check that your column header names are mapped to the correct Global Schema category. The pencil icon in the “Normalized Column” field should be gray, and the Global Schema category should be selected from the dropdown menu, not manually input.

Normalizing for Activation

If you’re planning to use any address column as an activation key, please toggle on the ‘export column’ toggle. 

Next steps

After normalizing the rest of your dataset you can prepare and publish to a new or existing Dataset.