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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.
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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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Given 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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How does CRM Analytics support versioning for dataflows?
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Recipes and dataflows are both used in CRM Analytics but serve different purposes. Dataflows combine data from multiple sources while recipes perform transformations on single datasets. Converting between them involves version constraints and conversion details that track what changes during the process.