The Salesforce CRM Analytics and Einstein Discovery Consultant exam preparation guide is designed to provide candidates with necessary information about the CRM Analytics and Einstein Discovery Consultant exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the Salesforce Certified CRM Analytics and Einstein Discovery Consultant exam.
It is recommended for all the candidates to refer the CRM Analytics and Einstein Discovery Consultant objectives and sample questions provided in this preparation guide. The Salesforce CRM Analytics and Einstein Discovery Consultant certification is mainly targeted to the candidates who want to build their career in Salesforce Consultant domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual Salesforce CRM Analytics and Einstein Discovery Consultant exam.
Salesforce CRM Analytics and Einstein Discovery Consultant Exam Summary:
|
Exam Name
|
Salesforce CRM Analytics and Einstein Discovery Consultant |
| Exam Code | CRM Analytics and Einstein Discovery Consultant |
| Exam Price |
Registration fee: USD 200 Retake fee: USD 100 |
| Duration | 90 minutes |
| Number of Questions | 60 |
| Passing Score | 65% |
| Recommended Training / Books |
Building Lenses, Dashboards, and Apps in CRM Analytics (ANC201) Implement and Manage CRM Analytics (ANC301) |
| Schedule Exam | Kryterion Webassessor |
| Sample Questions | Salesforce CRM Analytics and Einstein Discovery Consultant Sample Questions |
| Recommended Practice | Salesforce Certified CRM Analytics and Einstein Discovery Consultant Practice Test |
Salesforce CRM Analytics and Einstein Discovery Consultant Syllabus:
| Section | Objectives | Weight |
|---|---|---|
| Admin/Configuration |
- Given business and access requirements, enable CRM Analytics along with its features, encompassing permission sets and licenses. - Given a scenario, use CRM Analytics to design a solution that accommodates data sync/dataflows/recipes limits. - Given a situation, demonstrate knowledge of what can be accomplished with the CRM Analytics API. - Given business requirements, migrate between different environments for deployment. |
17% |
| Data Layer |
- Given data sources, use Data Manager to extract and load the data into the CRM Analytics application to create datasets. - Given business needs and consolidated data, implement refreshes for data syncs and dataflows/recipes while keeping limits and considerations in mind. - Given business/user requirements, perform data transformations in dataflows/recipes. - Given user requirements or ease of use strategies, manage dataset extended metadata (XMD) by editing labels, values, and colors. - Implement delivery management strategies in dataflows/recipes including versioning and conversion. |
23% |
| Security |
- Given governance and CRM Analytics asset security requirements, implement necessary security settings for users, groups, and profiles. - Given row-based security requirements, implement the appropriate dataset security settings by using sharing inheritance and security predicates. - Implement app sharing based on user and group requirements. |
16% |
| Analytics Dashboard Design |
- Given business requirements, scope, validate, and prioritize dashboard design requirements. - Create appropriate dashboards to meet business requirements following CRM Analytics best practices and UX design principles. - Identify the appropriate use and configuration of a standard CRM Analytics templated app to meet business requirements. |
13% |
| Analytics Dashboard Implementation |
- Given business requirements, configure dashboards using accurate query types and widget level parameters. - Given business requirements, develop selection/result interactions with different types of queries. - Given business requirements, use advanced functionality such as windowing and time series analysis within compare tables. - Given business requirements, make dashboards actionable and accessible in Lightning pages. - Given a scenario, monitor and optimize query performance using Dashboard Inspector. - Implement delivery management strategies using versioning and/or Dashboard Publisher. |
19% |
| Einstein Discovery |
- Build a model by assessing data and selecting one of the three types of predictions (numeric, binary, multi-classification). - Given business requirements, analyze the model results and propose data improvements to the customer. - Given derived results and insights from the model, adjust data parameters and add/remove data or columns to improve the model. - Enable prediction features on Lightning record pages across Salesforce and CRM Analytics. - Monitor and interpret a Model Card to improve or maintain model performance. |
12% |