Incremental User Report (Job API)

Overview

Adobe Learning Manager’s Incremental User Report is a new Job API feature that lets administrators and integration developers export only the users whose data has changed within a specified date-and-time window. Instead of pulling the complete user list every time, you can request a targeted slice covering only new or modified users.

This document covers:

Why use Incremental Reporting

This section explains the motivation for the feature and should help you decide whether incremental or full exports best fit your integration.

The problem with Full User Exports

The current full user export (generateUsers job type) returns every user in an account with every execution. For large enterprise accounts this creates two significant problems:

When to Use Incremental Reporting

Use the incremental export when you need to keep an external system synchronized with Adobe Learning Manager user data. Typical use cases:

Use the full export (generateUsers) when you need an authoritative baseline – for example, on first setup or after a long gap between syncs.

Current Full User Report

(generateUsers) This section documents the existing Job API user report for reference. If you are already familiar with it, skip to the next section.

How It Works

The current user CSV report is submitted as a job via the Jobs API. A Snaplogic pipeline picks up the task, executes a MySQL query against the CAPTIVATE database (user, usergroup, usergroup_user tables), and generates a CSV file.

Available Filters

The payload supports three optional filters:

CSV Columns

The exported CSV contains the following columns:

internalUserID, userEmail, customerDefinedUniqueUserId, name, managerEmail,

userType, state, excludedFromGamification, pointsEarned, profile, roles,

dateCreated, lastLoginDate, dateDeleted, uiLocale, contentLocale,

timeZoneCode, userSource, group, AF_location, AF_login, AF_externalaf,

lastSocialActivityDate

Request Payload

Job type: generateUsers. Admin role only.

{

  "data": {

    "type": "job",

    "attributes": {

      "description": "<description of your choice>",

      "jobType": "generateUsers",

      "payload": {

        "expandMetadata": "<true to export metadata as separate column>",

        "fetchActiveUsers": "<true to export ACTIVE users only>",

        "peerAccountId": "<peerAccountId for peer account report>"

      }

    }

  }

}

Limitations

Incremental User Report (generateUserIncrementalReport)

This section documents the newly introduced feature - Incremental User Report feature.

What Is an Incremental Export?

An incremental export returns only users whose tracked data has changed within a specified start and end date-time window. The backend stores a last-modified timestamp for each user’s tracked fields. When you request a report for a given window, only users whose most recent change falls within that window are included.

How the Change-Tracking Model Works

Adobe Learning Manager maintains a last-modified timestamp that is updated whenever any tracked field for a user changes.

When you request an incremental report with a start_date_time and end_date_time, the system returns users whose last-modified timestamp falls within [start_date_time, end_date_time]. If a user was modified both within and after the window (i.e., they were changed again after end_date_time), that user is not included in the report – because their last-modified timestamp is now beyond the window.

Fields tracked for changes

A user is included in an incremental report if any of the following fields changed:

Fields NOT Tracked for Changes

The following fields appear in the CSV output but do not trigger inclusion in an incremental export when they change:

Output Format

The incremental CSV report has the same columns and format as the full user CSV report. All columns appear in the same order, including all active field and metadata columns – regardless of which fields changed for the exported users.

New Job API for Incremental User Report

The incremental user report uses the Job API to generate a CSV file that contains users whose tracked data changed within the specified date-and-time window. For large result sets, use the same pagination model described later in this document: submit the same date window in each request and pass the last userId received in the previous response as fromUserId to retrieve the next chunk.

Job Type

Job type: generateUserIncrementalReport

Request Payload

{

    "data": {

        "type": "job",

        "attributes": {

            "description": "description of your choice",

            "jobType": "generateUserIncrementalReport",

            "payload":{

                 "fullExport": <Pass true to export all users. If fullExport is true, fromDate and toDate are ignored>,

                 "expandMetadata": <Pass true to export metadata as separate columns>,

                 "fromDate": <Start of the change window in ISO format, for example 2020-01-01T18:30:00.000Z>,

                 "toDate": <End of the change window in ISO format, for example 2020-01-31T18:30:00.000Z>,

                 "fromUserId": <For paginated requests, pass the last userId received in the previous response>

            }

        }

   }

}

Payload Parameters

For incremental export, pass fromDate and toDate to define the change window. If the result set is larger than one chunk, continue pagination by sending the same fromDate and toDate and passing the last userId from the previous response as fromUserId. If fullExport is true, the date window is ignored and the API generates a full user export.

Handling Large Accounts (500k+ Users)

User reports are generated using a data platform pipeline and output is returned in chunks to support large accounts. If an incremental export covers more than 500,000 users, the report is paginated.

Pagination Model

To retrieve all pages for a large incremental export, pass the same startDateTime and endDateTime in each request, and additionally pass the userId of the last user received in the previous chunk as fromUserId. The API will return the next set of up to 500,000 users with userId greater than the passed fromUserId.

Pagination Workflow

Step 1: Submit the first request without fromUserId.

// First request – no fromUserId

{

  "payload": {

    "startDateTime": "2026-05-01T00:00:00Z",

    "endDateTime": "2026-05-31T23:59:59Z"

  }

}

Step 2: Receive the first chunk (up to 500,000 users). Note the last userId in the response.

Step 3: Submit the next request, passing the same date window and the last userId from the previous response as fromUserId.

// Subsequent request – pass last userId from previous response as fromUserId

{

  "payload": {

    "startDateTime": "2026-05-01T00:00:00Z",

    "endDateTime": "2026-05-31T23:59:59Z",

    "fromUserId": "<last userId from previous response>"

  }

}

Step 4: Repeat until a response returns fewer than 500,000 records, indicating you have reached the last page.

Limitations

The incremental user report is intentionally scoped. The following capabilities are out of scope:

Connector integration

The incremental user report is designed to be used in Adobe Learning Manager connectors (PowerBI, Salesforce, and others) as a drop-in replacement for the full user report in regular sync pipelines. This allows connectors that today use generateUsers to migrate to the incremental model without changes to the downstream data schema.

Connectors can use the incremental report for delta-sync and fall back to the full report for bootstrap or recovery.