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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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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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Dataflows and recipes are both tools in CRM Analytics for preparing and transforming data, but they serve different purposes. Dataflows combine data from multiple sources to create datasets, while recipes perform transformations on datasets and output results to new target datasets.