#Automation50 discutindo

Hi all! I think I can't get around this but I'm wondering if anyone has any ideas. I have two lines of business (line a and line b) and line b wants to see some information from line a. Previously this has not been needed or possible. 

I have managed (using a looking field on the opportunity and a sharing rule) to make that happen. The problem is that if line b runs an account report (for example) they get line a info and we don't want that to happen. If I remove the sharing rule that makes this whole thing work - what I created falls apart. 

I'm thinking the only way is do something thing that would require a LOT of work and probably involve bringing in a developer - one or more of the following 

- custom dl account reference object 

- screen flow search 

- custom LWC 

anyone have any other thoughts/ideas? 

Thank you in advance as always for any help!  :) 

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!  

We have a process we're updating that involves sending out an automated email when a new record is created on a custom object.  Everything tested out in Sandbox, but when migrated to Prod, two slightly different emails are triggering when I test.  Talking with the internal customer, they said, "Yeah, that's always been going out," but they don't know who originally set it up.   

• It would have been set some time before me...but it's not triggering in Preprod, which has been refreshed recently - so I'd think it would.
• Checking Flow triggers, the only other flow triggering off of that custom object updates a field - there are no send email elements to it.
• I don't see any legacy email alerts or Workflow actions for it
• I turned off my Flow, opened a debug log on the automated process user, and nothing generated when I triggered that mystery email (that still came through.)

I'm kind of at a loss to figure out where to check from here. 

Anyone have any flows they are created to do either of these functions? 

Any resources out there that you know of?  

Would appreciate any comments 

so currently I'm making my own chatbot app, I'm training my own AI using machine learning and NLP for that app but how am I supposed to implement that AI model into Salesforce.. basically I want to make a UI and provide a database for that app, so what kind of salesforce technologies can help me to make a UI and to provide an overall backend + any additional tips?

#Sales Cloud #Salesforce Developer #Service Cloud #Experience Cloud #Integration #CRM Configuration #Automation 

Hello everyone

I need help to complete a unit in a trailmix set up case esclation project

Unit :create an automation with flow builder

I created the automation flow process but while I create the case to taste the flow

It gives me this message

And I tried to delete the flow , but it can't be deleted too!

Any help, please?

Thanks

I’m working with a Salesforce Flow that processes a relatively large number of records, and I’m looking for ways to improve its performance and reliability. 

The Flow currently performs several record queries and updates during execution. As the amount of data increases

the Flow takes longer to complete and can sometimes approach Salesforce governor limits. 

What are some recommended approaches for optimizing a Flow in this situation? For example, would reducing Get Records operations, using collections more effectively, or moving some logic to Apex help? 

I’d appreciate any practical suggestions or best practices for designing scalable Salesforce Flows.