(Beta) Use calculated fields to export arrays in flat schema files use-calculated-fields-to-export-arrays-in-flat-schema-files

Learn how to export arrays through calculated fields from Real-Time CDP in flat schema files to cloud storage destinations. Read this document to understand the use cases enabled by this functionality.

Get extensive information about calculated fields - what these are and why they matter. Read the pages linked below for an introduction to calculated fields in Data Prep and more information about all the available functions:

Arrays and other object types in Platform arrays-strings-other-objects

In Experience Platform, you can use XDM schemas to manage different field types. Previously, you were able to export simple key-value pair type fields such as strings out of Experience Platform to your desired destinations. An example of such a field that was supported for export previously is personalEmail.address:johndoe@acme.org.

Other field types in Experience Platform include array fields. Read more about managing array fields in the Experience Platform UI. In addition to the previously supported field types, you can now export array objects such as: organizations:[marketing, sales, engineering]. See further below extensive examples of how you can use various functions to access elements of arrays, join array elements into a string, and more.

Known limitations known-limitations

Note the following known limitations for the beta release of this functionality:

Prerequisites prerequisites

Connect to a desired cloud storage destination, progress through the activation steps for cloud storage destinations and get to the mapping step.

How to export calculated fields how-to-export-calculated-fields

In the mapping step of the activation workflow for cloud storage destinations, select (Beta) Add calculated field.

This opens a modal window where you can select attributes that you can use to export attributes out of Experience Platform.

For example, use the join function on the loyaltyID field as shown below to export an array of loyalty IDs as a string concatenated with an underscore in a CSV file. View more information about this and other examples further below.

Select Save to keep the calculated field and return to the mapping step.

Back in the mapping step of the workflow, fill in the Target field with a value of the column header you want for this field in the exported files.

When ready, select Next to proceed to the next step of the activation workflow.

Supported functions supported-functions

Note that only the following functions are supported in the beta release of calculated fields and array support for destinations:

Examples of functions used to export arrays examples

See examples and further information in the sections below for some of the functions listed above. For the rest of the listed functions, refer to the general functions documentation in the Data Prep section.

join function to export arrays join-function-export-arrays

Use the join function to concatenate the elements of an array into a string, using a desired separator, such as _ or |.

For example, you can combine the following XDM fields below as shown in the mapping screenshot by using a join('_',loyalty.loyaltyID) syntax:

In this case, your output file looks like below. Notice how the three elements of the array are concatenated into a single string using the _ character.

`First_Name,Last_Name,Personal_Email,Organization
John,Doe,johndoe@acme.org, "Marketing_Sales_Finance"

iif function to export arrays iif-function-export-arrays

Use the iif function to export elements of an array under certain conditions. For example, continuing with the organizations array object from above, you can write a simple conditional function like iif(organizations[0].equals("Marketing"), "isMarketing", "isNotMarketing").

In this case, your output file looks like below. In this case, the first element of the array is Marketing, so the person is a member of the marketing department.

`First_Name,Last_Name, Personal_Email, Is_Member_Of_Marketing_Dept
John,Doe, johndoe@acme.org, "isMarketing"

add_to_array function to export arrays add-to-array-function-export-arrays

Use the add_to_array function to add elements to an exported array. You can combine this function with the join function described further above.

Continuing with the organizations array object from above, you can write a function like source: join('_', add_to_array(organizations,"2023")), returning the organizations that a person is a member of in the year 2023.

In this case, your output file looks like below. Notice how the three elements of the array are concatenated into a single string using the _ character and 2023 is also appended at the end of the string.

`First_Name,Last_Name,Personal_Email,Organization_Member_2023
John,Doe, johndoe@acme.org,"Marketing_Sales_Finance_2023"

coalesce function to export arrays coalesce-function-export-arrays

Use the coalesce function to access and export the first non-null element of an array into a string.

For example, you can combine the following XDM fields below as shown in the mapping screenshot by using a coalesce(subscriptions.hasPromotion) syntax to return the first true of false value in the array:

In this case, your output file looks like below. Notice how the first non-null true value in the array is exported in the file.

First_Name,Last_Name,hasPromotion
John,Doe,true

size_of function to export arrays sizeof-function-export-arrays

Use the size_of function to indicate how many elements exist in an array. For example, if you have a purchaseTime array object with multiple timestamps, you can use the size_of function to indicate how many separate purchases were made by a person.

For example, you can combine the following XDM fields below as shown in the mapping screenshot.

In this case, your output file looks like below. Notice how the second column indicates the number of elements in the array, corresponding with the number of separate purchases made by the customer.

`Personal_Email,Times_Purchased
johndoe@acme.org,"5"

Index-based array access index-based-array-access

You can access an index of an array to export a single item from the array. For example, similar to the example above for the size_of function, if you are looking to access and export only the first time that a customer has purchased a certain product, you can use purchaseTime[0] to export the first element of the timestamp, purchaseTime[1] to export the second element of the timestamp, purchaseTime[2] to export the third element of the timestamp, and so on.

In this case, your output file looks like below, exporting the first time that the customer has made a purchase:

`Personal_Email,First_Purchase
johndoe@acme.org,"1538097126"

first and last functions to export arrays first-and-last-functions-export-arrays

Use the first and last functions to export the first or last element in an array. For example, continuing with the purchaseTime array object with multiple timestamps from the previous examples, you can use these to functions to export the first or the last purchase time made by a person.

In this case, your output file looks like below, exporting the first and the last time that the customer has made a purchase:

`Personal_Email,First_Purchase, Last_Purchase
johndoe@acme.org,"1538097126","1664327526"

Hashing functions hashing-functions

In addition to the functions specific for exporting arrays or elements from an array, you can use hashing functions to hash attributes in the exported files. For example, if you have any personally identifiable information in attributes, you can hash those fields when exporting them.

You can hash string values directly, for example md5(personalEmail.address). If desired, you can also hash individual elements of array fields, assuming elements in the array are strings, like this: md5(purchaseTime[0])

The supported hashing functions are: