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What is the duration, language, and format of Salesforce Mobile and Desktop Exploration in Einstein Analytics (ANC101) Exam
- Language of Exam: English
- Number of Questions: 85
- Duration of Exam: 120 minutes
- Passing Score: 70%
- Type of Questions: Multiple choice and scenario based
How to study the Salesforce Mobile and Desktop Exploration in Einstein Analytics (ANC101) Exam
Anyone, who is planning to write Salesforce Mobile and Desktop Exploration in Einstein Analytics (ANC101) Exam, should focus on their study material. So one of the questions is the platform from where they can get the right study material for their preparation. To get the right or valid material from online sources, they can refer some of the authorized websites. We understand its very difficult to get a genuine website from where student or participant can learn the right things so we recommend taking the ANC101 practice exams as they are the best source of preparation. We have already defined all of the course content so if you tried to explore it based on the course content it could be very easy for you to plan your study and prepare notes accordingly.
Preparation and study materials for the Salesforce Mobile and Desktop Exploration in Einstein Analytics (ANC101) Exam are provided by several online platforms including the Salesforce Trailhead official website for free and by certificate-questions in the form of ANC101 exam dumps. Interested candidates can simply search online with the name of the exam and can find learning materials. In order to use the material provided by Salesforce Trailhead, visit the links in the reference section of this document.
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Salesforce ANC-101 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Security and Access | - Sharing models and permissions - Security predicates - Row-level security |
| Topic 2: Analytics Discovery and Insights | - Einstein Discovery concepts - Predictive modeling usage |
| Topic 3: Data Modeling and Recipes | - Dataflows and recipes - Data transformation logic |
| Topic 4: Analytics Dashboard Design | - User experience and interactivity - Dashboard components and widgets - Filters and bindings |
| Topic 5: Data Management | - Data sources and ingestion - Data transformation and preparation - Dataset design and modeling |
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