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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.
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Given business needs and consolidated data, implement refreshes for data syncs and dataflows/recipes while keeping limits and considerations in mind.
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Given business/user requirements, perform data transformations in dataflows/recipes.
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What is the difference between a dataflow and a recipe in CRM Analytics?
Learn this conceptGiven user requirements or ease of use strategies, manage dataset extended metadata (XMD) by editing labels, values, and colors.
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Implement delivery management strategies in dataflows/recipes including versioning and conversion.
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The Flatten transformation traverses a self-referential hierarchy — such as a user role hierarchy or account parent hierarchy — by walking from each record upward through its parent chain until reaching the top-level record with no parent. It produces two output fields that represent that full ancestry path, enabling downstream security predicates and hierarchical rollups.