Checklist progress
0/196Learned
CRM Analytics and Einstein Discovery Consultant
Study Checklist
Checklist progress
0/196Learned
Given data sources, use Data Manager to extract and load the data into the CRM Analytics application to create datasets.
0/11
Given business needs and consolidated data, implement refreshes for data syncs and dataflows/recipes while keeping limits and considerations in mind.
0/9
What configuration is required to enable incremental sync for a Salesforce object in CRM Analytics?
Learn this conceptWhat happens when a CRM Analytics dataflow or recipe exceeds the platform's maximum allowed runtime?
Learn this conceptGiven business/user requirements, perform data transformations in dataflows/recipes.
0/13
Given user requirements or ease of use strategies, manage dataset extended metadata (XMD) by editing labels, values, and colors.
0/5
Implement delivery management strategies in dataflows/recipes including versioning and conversion.
0/4
Prepare for the Exam
Study Community
Ask questions and get the latest info from other CRM Analytics and Einstein Discovery Consultant studiers. 593 members and growing.
For local Salesforce objects (SFDC_Local connections), CRM Analytics incremental replication pulls new, updated, and soft-deleted records to match the source object since the last run, but it does not remove hard-deleted records. To capture hard deletions while maintaining incremental efficiency, configure the object's connection mode to Periodic Full Sync, which runs incremental syncs on each schedule and triggers a full sync periodically. For external connectors (Snowflake, S3), incremental sync is not available by default; full sync runs each time, so deleted records persist in the dataset until a recipe with a filter node explicitly excludes and overwrites them.