Adobe Experience Platform

We are attempting to create the edge audience using the Adobe API endpoint, but the profiles are not being qualified when we use streaming ingestion with the streaming API. However, when we manually create an edge audience through the UI, the profiles are being qualified when we use streaming ingestion API(Postman). These 2 Audience are manually created edge Audiences by using UI, but we don't see any API created audiences' qualification for the same data.

I need a correct roadmap to become Adobe Experience Platform developer to prepare my skills

I have created a Workspace Project Template which I intend to use for another of my organization which will also have the same schema and datasets, connections, dataviews. I have added a few calculated metrics in my Template. I was wondering how do I replicate the same Workspace Project using the Template for another Org ID using the calculated metrics I created previously?The idea here is to basically analyze the same structure of data in the same manner but for different organizations. Do the calculated metrics get copied from the Template?

Hi Team,I’m experiencing an issue where records deleted at the application level are not being fully removed from the Data Lake.Even after performing deletion, the data still appears to persist in the underlying storage. I’m unsure whether this is expected behavior due to delayed processing (e.g., background cleanup jobs, retention policies), or if it indicates a problem in the deletion workflow.Could anyone clarify:- Does deletion propagate asynchronously to the Data Lake?- Is there a recommended way to validate physical data cleanup?- Are there configurations that control this behavior?Any insights or best practices would be greatly appreciated.Thanks in advance!

I have got multiple companies under one AEP sandbox. These have separate data for each and one common for shred campaigns. Due to that some attributes might be nested at depth 5 (no primary ID, no relationships). In the documentation its said that performance guardrail is max 4 but for relationships and primary ids. Is 5 fine? What are your experiences?

We have Data coming from the source all the data relates to an event but we are not getting a timestamp from the source that is unique for each event it is same for couple of events relates to the different user what should we use for mapping in this case is it now() or timestamp for data prep

Can you give the solution to customize and create the RTE plugin for external link builder experience in RTE for AEM to add the anchor tag and have data-link-attrs for modal popup inside the a tag?

Hello everyone,we are based in Germany and are active users of Adobe Real-Time CDP Data Collaboration. You can find us in Adobe Collaboration as a collaborator.Our current primary Match Key is hashed email addresses from our publishers’ subscriber bases.iq digital media marketing gmbh is the exclusive marketer for leading media brands in Germany, covering general news, business & finance, trade media, and millennial‑focused content. Our portfolio includes well-known websites such as DER SPIEGEL, FAZ.NET, Handelsblatt Online, SZ.de, WirtschaftsWoche Online, and many more.We just startet. So far, we are very happy with the ease of use of Collaboration - and what is further to expect on the timeline here. It is easy to use and straightforward to operate, which we really appreciate. Therefore, we would like to invite advertisers and data providers who are already working with Adobe CDP to start a conversation about this new product (available in Europe since 2026) and to explore potent

Hey everyone — I built a free tool that might save you some time on your next AEP implementation.SynthAEP generates realistic XDM-compliant synthetic data for AEP sandboxes. Instead of manually crafting test profiles and events, you pick a scenario, set parameters, and download ready-to-ingest data.The multi-schema feature is what I'm most proud of: upload 2-5 schemas (mix of profile and event), choose batch or streaming format for each, and get a ZIP with unified data where identities stitch correctly across all datasets. Streaming exports come with Postman collections so you can POST directly to your DCS endpoint.Free tier available, custom/multi schema you can try once per day.aepsynthdata.comWould love to hear what would make this more useful for your workflows. What scenarios should I add? What field groups are missing?

Hi ​@Community I am working on AEP-SFMC API based destination connection. I have created a streaming type audience and activated it using SFMC API based connection. SFMC connection is set up successfully as I can see the target fields during mapping. On Audience activation profile get activated to destination.“Dataexport” is used as marketing action and no consent policy is used.Destination data flow runs and complete successfully but i get “Identities excluded” while profiles are received but none activated.“Identity excluded” comes with below description :  “The identities associated to some profiles cannot be exported to the destination due to missing user consent, or the consent provided by users does not match the consent settings applied to the destination. To respect user privacy, Experience Platform will not export these identities to this destination. For more information, refer to the Consent policy documentation: https://www.adobe.com/go/consent-policy-enforcement. “  I am n

Hi All,I’ve created a Custom schema and a dataset with a primary identity configured and enabled for lookup. The schema contains 20 attributes, of which 15 are marked as required.When I try to ingest data using the UI JSON upload, the UI throws an error with an empty message ("Add data is disabled because a required attribute is missing"). However, when I ingest the same data using other sources such as S3 or HTTP API ingestion, it works without any issues.Based on an AI search:Primary identity need to be correctly configured. This may be a UI-related limitation. The drag-and-drop JSON uploader seems to use a “simple ingestion” path, which does not support the same flexibility as dataflows (for example: mappings, transformations, defaults, conditional logic, or excluding empty keys). The platform may be performing a pre-validation and blocking the upload if it determines that required attributes cannot be guaranteed, even before actual ingestion.Is this a known issue, or are there spec

Hi all! Has anyone managed to successfully add and see custom validation results in the validation overview of an Assurance session?When creating and publishing custom validators, I still cannot see their results showing in the Assurance overview, however I do see the function showing in the dropdown when I go back into the validators. The validator is published and shows the (failing) results as expected on a given session. I just cannot see this in the overview and do not see a way to manually add this, so assume that this should come automatically? The documentation seems unfortunately extremely thin on this topic, Adobe...Newly created validator (published) Missing new validator in overview Validator as such when looked at within a specific session correctly shows validation errorsCheers from Switzerland 

If I create Data Type with API its not editable in UI? Is it standard behaviour?

I have relationship between these two schemas: profile schema with ID of user’s favourite petrol station  non profile schema with relationship to schema from point A. All the details about petrol station - what is available etc Does it make sense to use the schema from point B as a lookup schema in AJO? 

Just a quick question - can someone help us to understand if Dynamic Datastream rerouting occurs after datastream transformations? or if this happens before? I assume its afterwards but I wanted confirmation. Thanks,Ty

 After a recent upgrade of the OneTrust Consent Management for Cookies extension in Adobe Launch, we started encountering the following runtime error:Uncaught Error: [OptIn] Invalid category(-ies). Please use the `OptIn.Categories` enum.This error was not present before the extension upgrade and now occurs consistently after publishing the new build. Observations✅ Previous OneTrust Extension Version (working)In the older version of the OneTrust extension, the generated custom code configuration looked like this: JSON {"otConfiguration": {}}``Show more linesThere were no undefined Adobe categories, and Adobe Opt‑In worked as expected.❌ New OneTrust Extension Version (after upgrade)After upgrading the OneTrust extension, the generated configuration now looks like the following:  {"autoLoadScript": false,"otConfiguration": {"adobeCat_0": "undefined","adobeCat_1": "undefined","adobeCat_2": "undefined","adobeCat_3": "undefined","adobeCat_4": "undefined","adobeCat_5": "undefined","adobeCat_6

Hello Community,I have a clarification question related to datetime formatting in Adobe Experience Platform (AEP) using Data Prep.From the source file, we receive the datetime value as a string in the following format:2026-04-10 14:23:56My requirement is to ingest this into AEP as a datetime/timestamp field, but with the date represented in MM‑DD‑YYYY order, for example:04-10-2026 14:23:00The primary concern here is whether AEP allows transforming and storing the datetime in MM‑DD‑YYYY HH:mm:SS format, instead of the default YYYY‑MM‑DD.I understand that AEP standardizes timestamps internally, but I would like to confirm:Is it technically possible in AEP Data Prep to store a datetime with the MM‑DD‑YYYY date order? If not, is this format strictly limited to parsing at ingestion ? What would be the recommended best practice in this scenario?Any guidance or confirmation from the community would be very helpful.Thank you!

​@AmitVishwakarma ​@Asheesh_Pandey ​@kautuk_sahni ​@akshay_kashyap Any suggestions would be appreciated thank you Hi Folks,Based on the referenced document, I created a date filter to limit ingestion from a Snowflake table that contains the last 10 years of historical data. The requirement was to ingest only the last one month of data initially and then continue with incremental ingestion going forward.The initial load completes successfully, and we can see the expected data in AEP. However, during the incremental runs, the dataflow fails to ingest any new records, even though new data is available in Snowflake.It appears that the delta column–based incremental logic is not picking up the latest data, resulting in no records being ingested during incremental executionsPQL filter in the Source connection works as expected !--scriptorstartfragment-->{  "type": "PQL",  "format": "pql/json",  "value": {    "nodeType": "fnApply",    "fnName": ">=",    "params": [      {        "nodeTy

According to the official documentation, for B2C implementations, the Schema Editor UI only allows configuring one-to-one relationships between schemas:Define a Relationship Between Two Schemas Using the Schema Editor | Adobe Experience PlatformI would like to clarify the following: Is it possible to define one-to-many or many-to-many relationships between XDM schemas using the Schema Registry API? If this is not supported (neither via UI nor API), what is the recommended modeling approach in AEP to represent these relationships? Denormalization into the primary schema? Use of lookup datasets? Use of ExperienceEvent schemas with references? Are there any limitations or implications for Real-Time Customer Profile or segmentation when modeling these types of relationships? Any guidance or best practices for handling one-to-many or many-to-many relationships in B2C AEP implementations would be greatly appreciated.Thanks in advance.

Is there a way to define a timeout for a ITAS/CTAS query? Out of the box timeout is 24 hours but I’d like to limit that to 5 hours, preferably on query level? Cheer,Mauri

My connection to the PostgreSQL database  for the Query Service has been giving me this errorErrorCode: 08P01 queryId: 07326d38-0746-48c6-8332-17b75c01dac2 Unknown error encountered. Reason: [Embedded Postgres: Error while populating metadata tables in embedded Postgres]This was not happening before until 2weeks ago.My solution uses psycopg2 library to connect to query services.  conn = psycopg2.connect(                f"sslmode=require host={hostname} port=5432 dbname={database}?FLATTEN user={user} password={password}"I’m completely not sure what the issue as this setup has being running for almost a year. 

Is the Embedded feature of the Postgresql db deprecated. I’m table about the ?FLATTEN that enable access to metadata tables.conn = psycopg2.connect(f"sslmode=require host={hostname} port=5432 dbname={database}?FLATTEN user={user} password={password}")This doesn’t seem to work anymore. Any clue

​@AmitVishwakarma ​@Asheesh_Pandey ​@kautuk_sahni ​@akshay_kashyap Hi Folks,Based on the referenced document, I created a date filter to limit ingestion from a Snowflake table that contains the last 10 years of historical data. The requirement was to ingest only the last one month of data initially and then continue with incremental ingestion going forward.The initial load completes successfully, and we can see the expected data in AEP. However, during the incremental runs, the dataflow fails to ingest any new records, even though new data is available in Snowflake.It appears that the delta column–based incremental logic is not picking up the latest data, resulting in no records being ingested during incremental executionsPQL filter in the Source connection works as expected !--scriptorstartfragment-->{  "type": "PQL",  "format": "pql/json",  "value": {    "nodeType": "fnApply",    "fnName": ">=",    "params": [      {        "nodeType": "fieldLookup",        "fieldName": "busine

We are running into challenges where a person is merging duplicate records in SFDC, and SFDC sets the score with the winning record. However, when it syncs to Marketo is sums (aka doubles) the score. Trying to figure out a workaround as this is causing false MQLs to trigger to sales. This is because our MQL programs are triggered based off the person score hitting a certain threshold.Any insights?