Create an Adobe Analytics source connection in the UI

This tutorial provides steps for creating an Adobe Analytics source connection in the UI to bring Adobe Analytics report suite data into Adobe Experience Platform.

Getting started

This tutorial requires a working understanding of the following components of Experience Platform:

  • Experience Data Model (XDM) System: The standardized framework by which Experience Platform organizes customer experience data.
  • Real-Time Customer Profile: Provides a unified, real-time consumer profile based on aggregated data from multiple sources.
  • Sandboxes: Experience Platform provides virtual sandboxes which partition a single Platform instance into separate virtual environments to help develop and evolve digital experience applications.

Key terminology

It is important to understand the following key terms used throughout this document:

  • Standard attribute: Standard attributes are any attribute that is pre-defined by Adobe. They contain the same meaning for all customers and are available in the Analytics source data and Analytics schema field groups.
  • Custom attribute: Custom attributes are any attribute in the custom variable hierarchy in Analytics. Custom attributes are used within an Adobe Analytics implementation to capture specific information into a report suite, and they can differ in their use from report suite to report suite. Custom attributes include eVars, props, and lists. See the following Analytics documentation on conversion variables for more information on eVars.
  • Any attribute in Custom field groups: Attributes that originate from field groups created by customers are all user-defined and are considered to be neither standard nor custom attributes.
  • Friendly names: Friendly names are human-provided labels for custom variables in an Analytics implementation. See the following Analytics documentation on conversion variables for more information on friendly names.

Create a source connection with Adobe Analytics


When you create an Analytics source dataflow in a production sandbox, two dataflows are created:

  • A dataflow that does a 13-month backfill of historical report suite data into data lake. This dataflow ends when the backfill is complete.
  • A dataflow flow which sends live data to data lake and to Real-Time Customer Profile. This dataflow runs continuously.

In the Platform UI, select Sources from the left navigation to access the Sources workspace. The Catalog screen displays a variety of sources that you can create an account with.

You can select the appropriate category from the catalog on the left-hand side of your screen. You can also use the search bar to narrow down the displayed sources.

Under the Adobe applications category, select Adobe Analytics and then select Add data.


Select data


The report suites listed on the screen may come from various regions. You are responsible for understanding the limitations and obligations of your data and how you use that data in Adobe Experience Platform cross regions. Please ensure this is permitted by your company.

The Analytics source add data step provides you with a list of Analytics report suite data to create a source connection with.

A report suite is a container of data that forms the basis of Analytics reporting. An organization can have many report suites, each containing different datasets.

You can ingest report suites from any region (United States, United Kingdom, or Singapore) as long as they are mapped to the same organization as the Experience Platform sandbox instance in which the source connection is being created in. A report suite can be ingested using only a single active dataflow. A report suite that is not selectable has already been ingested, either in the the sandbox that you are using or in a different sandbox.

Multiple in-bound connections can be made to bring multiple report suites into the same sandbox. If the report suites have differing schemas for variables (such as eVars or events), they should be mapped to specific fields in the custom field groups and avoid data conflicts using Data Prep. Report suites can only be added to a single sandbox.


Data from multiple report suites can be enabled for Real-Time Customer Profile only if there are no data conflicts, such as two custom properties (eVars, lists and props) that have different meaning.

To create an Analytics source connection, select a report suite and then select Next to proceed.



Data Prep transformations may add latency to the overall dataflow. The additional latency added varies based on the complexity of the transformation logic.

Before you can map your Analytics data to target XDM schema, you must first select whether you are using a default schema or a custom schema.

A default schema creates a new schema on your behalf, containing the Adobe Analytics ExperienceEvent Template field group. To use a default schema, select Default schema.


With a custom schema, you can choose any available schema for your Analytics data, as long as that schema has the Adobe Analytics ExperienceEvent Template field group. To use a custom schema, select Custom schema.


The Mapping page provides an interface to map source fields to their appropriate target schema fields. From here, you can map custom variables to new schema field groups and apply calculations as supported by Data Prep. Select a target schema to start the mapping process.


Only schemas that have the Adobe Analytics ExperienceEvent Template field group are displayed in the schema selection menu. Other schemas are omitted. If there are no appropriate schemas available for your Report Suite data, then you must create a new schema. For detailed steps on creating schemas, see the guide on creating and editing schemas in the UI.


The Map standard fields section displays panels for Standard mappings applied, Non matching standard mappings and Custom mappings. See the following table for specific information regarding each category:

Map standard fields Description
Standard mappings applied The Standard mappings applied panel displays the total number of mapped attributes. Standard mappings refer to mapping sets between all attributes in the source Analytics data and corresponding attributes in Analytics field group. These are pre-mapped and cannot be edited.
Non matching standard mappings The Non matching standard mappings panel refers to the number of mapped attributes that contain friendly name conflicts. These conflicts appear when you are re-using a schema that already has a populated set of field descriptors from a different Report Suite. You can proceed with your Analytics dataflow even with friendly name conflicts.
Custom mappings The Custom mappings panel displays the number of mapped custom attributes, including eVars, props, and lists. Custom mappings refer to mapping sets between custom attributes in the source Analytics data and attributes in custom field groups included in the selected schema.


To preview the Analytics ExperienceEvent template schema field group, select View in the Standard mappings applied panel.


The Adobe Analytics ExperienceEvent Template Schema Field Group page provides you with an interface to use for inspecting the structure of your schema. When finished, select Close.


Platform automatically detects your mapping sets for any friendly name conflicts. If there are no conflicts with your mapping sets, select Next to proceed.



If there are friendly name conflicts between your source Report Suite and your selected schema, you can still continue with your Analytics dataflow, acknowledging that the field descriptors will not be changed. Alternatively, you can opt to create a new schema with a blank set of descriptors.

Custom mappings

You can use Data Prep functions to add new custom mapping or calculated fields for custom attributes. To add custom mappings, select Custom.


Depending on your needs, you can select either Add new mapping or Add calculated field and proceed to create custom mappings for your custom attributes. For comprehensive steps on how to use Data Prep functions, please read the Data Prep UI guide.

The following documentation provides further resources on understanding Data Prep, calculated fields, and mapping functions:

Filtering for Real-Time Customer Profile

Once you have completed mappings for your Analytics report suite data, you can apply filtering rules and conditions to selectively include or exclude data from ingestion to the Real-Time Customer Profile. Support for filtering is only available for Analytics data and data is only filtered prior to entering Profile. All data are ingested into the data lake.

Row-level filtering


Use row-level filtering to apply conditions and dictate which data to include for Profile ingestion. Use column-level filtering to select the columns of data that you want to exclude for Profile ingestion.

You can filter data for Profile ingestion at the row-level and the column-level. Row-level filtering allows you to define criteria such as string contains, equals to, begins, or ends with. You can also use row-level filtering to join conditions using AND as well as OR, and negate conditions using NOT.

To filter your Analytics data at the row-level, select Row filter.


Use the left rail to navigate through the schema hierarchy and select the schema attribute of your choice to further drill down a particular schema.


Once you have identified the attribute that you want to configure, select and drag the attribute from the left rail to the filtering panel.


To configure different conditions, select equals and then select a condition from the dropdown window that appears.

The list of configurable conditions include:

  • equals
  • does not equal
  • starts with
  • ends with
  • does not end with
  • contains
  • does not contain
  • exists
  • does not exist


Next, enter the values that you want to include based on the attribute that you selected. In the example below, Apple and Google are selected for ingestion as part of the Manufacturer attribute.


To further specify your filtering conditions, add another attribute from the schema and then add values based on that attribute. In the example below, the Model attribute is added and models such as the iPhone 13 and Google Pixel 6 are filtered for ingestion.


To add a new container, select the ellipses (...) on the top right of the filtering interface and then select Add container.


Once a new container is added, select Include and then select Exclude from the dropdown window that appears.


Next, complete the same process by dragging schema attributes and adding their corresponding values that you want to exclude from filtering. In the example below, the iPhone 12, iPhone 12 mini, and Google Pixel 5 are all filtered from exclusion from the Model attribute, landscape is excluded from the Screen orientation, and model number A1633 is excluded from Model number.

When finished, select Next.


Column-level filtering

Select Column filter from the header to apply column-level filtering.


The page updates into an interactive schema tree, displaying your schema attributes at the column-level. From here, you can select the columns of data that you would like to exclude from Profile ingestion. Alternatively, you can expand a column and select specific attributes for exclusion.

By default, all Analytics go to Profile and this process allows for branches of XDM data to be excluded from Profile ingestion.

When finished, select Next.


Provide dataflow details

The Dataflow detail step appears, where you must provide a name and an optional description for the dataflow. Select Next when finished.



The Review step appears, allowing you to review your new Analytics dataflow before it is created. Details of the connection are grouped by categories, including:

  • Connection: Displays the source platform of the connection.
  • Data type: Displays the selected Report Suite and its corresponding Report Suite ID.


Monitor your dataflow

Once your dataflow has been created, you can monitor the data that is being ingested through it. From the Catalog screen, select Dataflows to view a list of established flows associated with your Analytics account.


The Dataflows screen appears. On this page is a pair of dataset flows, including information about their name, source data, creation time, and status.

The connector instantiates two dataset flows. One flow represents backfill data and the other is for live data. Backfill data is not configured for Profile but is sent to the data lake for analytical and data-science use-cases.

For more information on backfill, live data, and their respective latencies, see the Analytics Data Connector overview.

Select the dataset flow you wish to view from the list.


The Dataset activity page appears. This page displays the rate of messages being consumed in the form of a graph. Select Data governance from the top header to access the labelling fields.


You can view a dataset flow’s inherited labels from the Data governance screen. For more information on how to label data coming from Analytics, visit the data usage labels guide.


To delete a dataflow, head to the Dataflows page and then select the ellipses (...) beside the dataflow name and then select Delete.


Next steps and additional resources

Once the connection is created, the dataflow is automatically created to contain the incoming data and populate a dataset with your selected schema. Furthermore, data back-filling occurs and ingests up to 13 months of historical data. When the initial ingestion completes, Analytics data and be used by downstream Platform services such as Real-Time Customer Profile and Segmentation Service. See the following documents for more details:

The following video is intended to support your understanding of ingesting data using the Adobe Analytics Source connector:


The Platform UI shown in the following video is out-of-date. Please refer to the documentation above for the latest UI screenshots and functionality.

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