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#Data36045 discutindo

 Agentforce enforces a 120-second (2-minute) maximum response time

per agent turn. If the agent doesn't complete its reasoning, tool calls, and response generation within that window, the session times out the error message leaving no trace in the STDM.  

 

What we've checked:

  • No timeout text in ErrorMessageText or OutputValueText
  • AiAgentSessionEndType is NOT_SET for every session, so it's not usable
  • Step durations show no spike near 120s; the killed step appears not to be recorded

Current approach: infer timeouts per interaction as "user Input with no agent Output." Complication: Output messages outnumber Inputs ~2:1, so welcome or progress messages may hide real timeouts.

Questions:

  1. Is there any STDM field or event that records a turn-level timeout?
  2. How are others separating timeouts from user abandonment?
  3. Is a timeout signal on the roadmap for Session Tracing?

#Agentforce

 

 

#Data360

3 respostas
  1. 3 de out., 08:06

    @Mudit Mishra

     

     

    This is where I’d avoid relying on message counts alone. With welcome/progress messages, Input → Output isn’t a reliable indicator of a completed turn.

    I’d correlate the interaction ID across STDM and channel/API logs, then classify it as completed, abandoned, or suspected timeout. The bigger gap here is really observability at the agent-turn level.

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Hello Trailblazer Community,

I'm working on a Salesforce Data 360 POC connected to my B2B Store Salesforce org.

In Data Explorer, selecting the Shopping Cart Engagement Data Model Object produces this error:

Something's not right with the query. Check the columns or filter and try again.

  • Data Space: default
  • Error code: -1719234624
  • Latest GackId: 11768440-431849
  • WebCart Data Lake Object: records are visible.
  • WebCart stream: Active; latest refresh status shows Success.
  • Other Data Model Objects open successfully.
  • The error persists after reducing the selected columns.

Has anyone encountered this issue, and what steps resolved it?

Thank you. 

 

Data 360 Data Explorer error when opening Shopping Cart Engagement DMO

 

 

 

#Data Cloud  #Data360  #Data Management

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Hello 

 

Delete data graph data cloud

 

I'm trying to delete my data graph so I can modify the relationships in the data model. Without deleting it, I won't be able to modify the relationships. 

But I still have these two dependencies that are preventing me from deleting it. I've already deleted all the forms and landing pages. It must be stored somewhere or something like that, because I can't delete it. Do you have any ideas, please? 

 

#Data Cloud  #Data360

3 respostas
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Hi Everyone, 

 

I am unable to complete the "Add to the Data Model Object" challenge from the Superbadge: Data Stream Fundamentals. 

 

The Error comes out as: "Whoops, looks like there was a problem. Please try again." 

 -I tried to redo the entire challenge but same error message comes out.  

- created a field called "International Contact" in the Account Contact DMO as per instructions and requirement.  

- Double checked the DMO if there's a same field name or something, but unable to find any duplicate field. 

- I labeled my org playground as "Superbadge - Data Stream Fundamentals - Developer Edition" in case someone becomes confused with the error message.

Unable to complete the

Not sure what else I could have missed.  

 

Thank you in Advance Trailblazers! 

 

#Trailhead Challenges  #Data Cloud  #Data360

3 respostas
  1. 29 de set., 13:09

    Hello @Antonio Bianco Ignacio

     

    You can try the following options:

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My team is currently pulling report data available from the Marketing Cloud Engagement data views, based on the documentation list, but we haven't found any documentation on whether the same report is also available in Marketing Cloud Next? 

 

For the reference: 

https://help.salesforce.com/s/articleView?id=mktg.mc_as_data_views.htm&type=5

 

 

Thank you 

 

#Marketing Cloud  #Data360

1 resposta
  1. 27 de set., 15:36

    Hi Sabrang, 

     

    Marketing Cloud Engagement Data Views and Marketing Cloud Next use different data models, so the Engagement Data Views listed in the documentation aren’t necessarily available as the same views in Marketing Cloud Next. 

     

    For Next, I’d check the corresponding Data Cloud/Data 360 DMOs and reporting capabilities for the specific data you’re trying to retrieve. Some Engagement data is available through different objects or data streams rather than through the traditional _Sent, _Open, _Click, etc. Data Views. 

     

    If you share the specific Data Views/report fields you need, it would be easier to identify the closest Marketing Cloud Next equivalent and whether the data is available directly or needs to be surfaced through Data Cloud.

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Good afternoon everyone, hope you're doing well.

 

I'm currently having trouble running Push and InApp tests in Marketing Cloud Next. Salesforce informed us that the contact needs to be mapped to the Contact Point App DMO.

We did the DMO mapping correctly, but even so, the users still aren't populating in our DMO, and we haven't received any of the test messages. Do you know if there is a mandatory field that needs to be filled out? Or if we might have missed a configuration step during the process?

 

Note: The goal is to successfully perform these send tests (push and in-app) in Marketing Cloud Next. If you have any real-world scenarios, documentation, or use cases to share, it would help us a lot. 

 

Thank you! 

 

#Trailhead  #Salesforce Developer  #Salesforce Admin  #Salesforce  #TrailblazerCommunity  #Marketing Cloud  #Data360

1 resposta
  1. 27 de set., 13:04

    Hi Guilherme,

    If the Contact Point App DMO mapping is already configured, I’d check the data ingestion and identity resolution side next. Make sure the required contact/app identifiers are populated and that the contact is correctly unified with the Contact Point App record. 

     

    I’d also verify that the mobile app is properly configured for push notifications and that the test user/device is registered and associated with the expected contact. If the DMO is still not receiving records, checking the ingestion/mapping status and any Data Cloud processing errors should help identify where the data flow is stopping. 

     

    If you can share the DMO mapping, the fields you’re populating for the test contact, and any errors shown during ingestion or testing, it would be easier to pinpoint the missing configuration. 

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Hello, 

This module seems bugged:

https://trailhead.salesforce.com/fr/content/learn/modules/data-cloud-in-flows/set-up-a-custom-data-cloud-playground?journey=data-360&trail_id=data-cloud-explore-setup-to-activation

 

Step 1: Create Data Streams from a Data Kit

-> this one works fine 

 

Step 2: Create a Calculated Insight

-> this one doesnt work 

 

If i create from kit just like trailhead request to do it i have this: 

 

 i verified the following: 

- Data 360 sync user does have access to the custom salesforce objects 

- i have all existing permission set possible assigned to me 

- the dmos do exist  with ready status

 

so I tried 2 things: 

- Recreate multiple playground, no success, always same error 

- Create by myself the calculated insight through the builder (following what the sql is doing) 

for latest option i have still an issue running the insight 

Capture d’écran 2026-09-13 à 15.07.07.png

 

any idea guys? thank you

 

#Trailhead Challenges  #Data360  #Data Cloud  #Trailhead

2 respostas
  1. 22 de set., 19:04

    Hi i got a response from trailhead team, they decided to remove the module from the platform because it was bugged. 

    Will probably be offline for a while

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Hi everyone,

I am designing a Data Cloud flow where a CRM staging object is regularly purged due to retention rules. In Data Cloud, we need to keep the processed data in a permanent target table for audit purposes, even after the source records are deleted.

With UI-based Batch Data Transforms, platform-managed Full Refreshes periodically rebuild the target table from scratch based only on current source data. This would wipe out our historical target records once the source is purged.

I want to confirm how Python Custom Code Extensions (PySpark SDK) handle this:

  1. When using client.write_to_dmo(..., write_mode=WriteMode.APPEND), does PySpark strictly append new rows without ever wiping or truncating the target table?
  2. Is PySpark execution completely immune to automatic platform Full Refreshes, meaning Data Cloud will never automatically wipe and rebuild a target table written via Custom Code?
  3. Under WriteMode.MERGE, if a record is deleted from the source table, can we confirm it remains untouched in the target table rather than being deleted?

Has anyone implemented this pattern for keeping permanent history from short-lived staging sources in Data Cloud?

Thanks!  

 

#Data360  #Automation

2 respostas
  1. 21 de set., 20:46

    Hi Alessandro,

    Regarding your design pattern for preserving historical audit records from short-lived staging sources in Data Cloud, here are the technical confirmations for how PySpark Custom Code Extensions handle write operations: 

     

    1.WriteMode.APPEND Execution:Append Behavior. 

    When using client.write_to_dmo(..., write_mode=WriteMode.APPEND), PySpark strictly appends new incoming rows to the target Data Model Object (DMO) or Data Lake Object (DLO) without truncating or wiping existing data. It will never automatically rebuild or clear out historical rows. 

     

    2.Immunity to Full Refreshes:Platform Independence. 

    PySpark code execution is completely separate from the platform-managed Full Refresh schedules used by standard UI Batch Data Transforms. Data Cloud will not automatically trigger a full rebuild or drop table operation on targets populated via Custom Code Extensions. 

     

    3.WriteMode.MERGE and Source Deletions:Merge Behavior on Deletions. 

    Under WriteMode.MERGE, records that are deleted or purged from the source staging table remain untouched and preserved in the target table. Merge updates or inserts matching records based on keys, but it does not propagate source deletions to remove historical records from the target.

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Hello,

I'm doing the trailhead module " https://trailhead.salesforce.com/content/learn/modules/data-cloud-in-flows/set-up-a-custom-data-cloud-playground?trail_id=prepare-for-your-salesforce-data-360-consultant-exam"  and when trying to create the calculated insight from a data kit as mentionned , i cannot activate it and have this error :

 

 

Review your expression errors and try again.

  • 1: Cannot find type for node External_Abandoned_Cart_c_Home__dlm.Id__c
  • 2: Cannot find type for node External_Abandoned_Cart_c_Home__dlm.Guest_ID_c__c
  • 3: Cannot find type for node External_Abandoned_Cart_c_Home__dlm.Guest_ID_c__c
  • 4: Cannot find type for node ssot__Individual__dlm.ssot__Id__c
  • 5: Cannot find type for node External_Abandoned_Cart_c_Home__dlm.CreatedDate__c
  • 6: GREATER_THAN_OR_EQUAL operator must have the same type of arguments on both sides
  • 7: Error getting FactTable ssot__Individual__dlm
  • 8: Error getting FactTable External_Abandoned_Cart_c_Home__dlm
  • 9: FullColumnName External_Abandoned_Cart_c_Home__dlm.Id__c cannot be found in dependencies or existing DMOs
  • 10: FullColumnName External_Abandoned_Cart_c_Home__dlm.Guest_ID_c__c cannot be found in dependencies or existing DMOs
  • 11: FullColumnName External_Abandoned_Cart_c_Home__dlm.CreatedDate__c cannot be found in dependencies or existing DMOs
  • 12: FullColumnName ssot__Individual__dlm.ssot__Id__c cannot be found in dependencies or existing DMOs

Can you help please 

 

 

  

 

#Trailhead Challenges  #Trailhead  #Data360

6 respostas
  1. 19 de set., 19:39

    1. Go to "Data Governance" tab 

    2. Delete the existing "Policies" listed on the left menu 

    3. Create a new policy with access to all objects for all users 

     

    Note: If "Data Governance" tab is not available, add "Data Cloud Architect" permission sets to your user.

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After completing all the steps I am getting this error while Verifying:

We can't find the Data Stream ‘Lead_Home’. Review the data streams to ensure the correct data streams have been created.

#Trailhead Challenges  #Data360

4 respostas
  1. 15 de set., 07:51

    Hi Pritesh, this one's usually just a deployment/naming issue, not a real bug in the challenge. 

     

    Lead_Home is one of the 6 data streams that gets auto-created when you deploy the Sales data bundle in the Create a Data Stream step (New > Salesforce CRM > View Bundles > Sales > Next > Next > Deploy). If the verifier can't find it, check these in order: 

     

    1. Deployment didn't finish. Deploys can take a few minutes. Go to the Data Streams tab and confirm Lead_Home actually shows up with a completed/active status, not still processing. If it's stuck, cancel and redeploy the Sales bundle. 

     

    2. Wrong path was used. Make sure you picked View Bundles (not View Objects) and selected the Sales bundle specifically — if you added Lead individually through View Objects, Salesforce sometimes won't auto-name it exactly Lead_Home, which breaks the check since it's looking for that exact name. 

     

    3. Deployed twice / renamed it. If you retried the deploy after a failure, you can end up with Lead_Home2 or a duplicate instead of Lead_Home. Delete the duplicate and make sure only one clean Lead_Home exists. 

     

    4. Wrong Data Space. Confirm it deployed to the default Data Space — the challenge checks there, so if you changed the space during setup it won't find it. 

     

    5. Wrong connected source. Double check you selected Salesforce CRM (not Marketing Cloud or another connector) for the source in step 3. 

     

    Fix: delete any bad/duplicate Lead_Home streams, redo New > Salesforce CRM > Sales bundle > Deploy, wait for it to finish (green/active status), then hit Verify Step again. 

     

    Reference:

    https://trailhead.salesforce.com/content/learn/projects/explore-data-cloud-core-functionality/create-data-streams-1

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