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| Section | Weight | Objectives |
|---|
| Topic 1: Data Layer | 23% | - Data Sources & Integration
- 1. Use Dataflows and Recipes for transformation
- 2. Define datasets and map Salesforce objects
- 3. Extract, load, and prepare data using Data Manager
- Data Management & Optimization
- 1. Implement data modeling and relationships
- 2. Resolve data sync and refresh issues
- 3. Optimize dataset performance
|
| Topic 2: Dashboard Design & Development | 25% | - Design Principles
- 1. Apply best practices for usability and performance
- 2. Design for mobile and Lightning compatibility
- Build & Configure Dashboards
- 1. Implement bindings, filters, and interactions
- 2. Use SAQL for advanced queries
- 3. Create lenses, steps, and visualizations
|
| Topic 3: Security & Access | 12% | - Sharing & Permissions
- 1. Implement row-level security and inheritance
- 2. Configure app, dataset, and field-level security
- 3. Manage user and group access
|
| Topic 4: Einstein Discovery | 22% | - Deployment & Usage
- 1. Interpret results and recommendations
- 2. Embed predictions in dashboards and Lightning pages
- 3. Monitor and maintain model performance
- Model Building & Configuration
- 1. Train, evaluate, and refine models
- 2. Prepare and assess data for modeling
- 3. Select prediction type: numeric, binary, multi-class
|
| Topic 5: Analytics Administration & Deployment | 18% | - Implementation & Maintenance
- 1. Manage versioning and deployment
- 2. Use Dashboard Inspector and Publisher
- 3. Monitor and optimize query performance
|
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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q92-Q97):
NEW QUESTION # 92
The marketing team at Cloud Kicks has five dashboards in an app. Four widgets are replicas of each other in three of the dashboards.
What is the best way to maintain these widgets?
- A. Create/Edit a lens and add each dashboard.
- B. Create/Edit the widgets individually on each dashboard.
- C. Create/Edit a component for the widgets.
Answer: C
Explanation:
To maintain consistency and ease of updates across multiple dashboards, creating or editing a component for the widgets is the most effective method. This approach:
Efficiency in Updates: Allows changes to be made in one place, which automatically propagates to all instances where the component is used across dashboards.
Consistency: Ensures uniformity in the appearance and functionality of the widgets across different dashboards.
Simplicity: Reduces the need for redundant work, where each widget would otherwise need to be updated individually.
NEW QUESTION # 93
A CRM Analytics consultant at Cloud Kicks wants to create a new dashboard that uses custom GeoJSON to display data; however, they are unable to upload the file via the user interface (UI).
Which action should the consultant take?
- A. Add the system permission "Manage Analytics Custom Maps" to the permission set used.
- B. Upload the GeoJSON via the API because it is NOT a function in the UI.
- C. Enable Custom maps with GeoJSON"" in the analytics settings.
Answer: B
Explanation:
If a consultant at Cloud Kicks needs to use custom GeoJSON files for dashboard visualization and cannot upload the file via the CRM Analytics user interface (UI), the recommended action is to use the API for this purpose. Here's why this approach is suggested:
* Functionality Limitation in UI: Currently, the CRM Analytics UI does not support direct uploads of GeoJSON files, which necessitates an alternative method.
* API Flexibility: The API provides a more flexible route for uploading custom GeoJSON files, allowing consultants to integrate more complex or larger datasets that are not supported through standard UI functionalities.
* Customization and Control: Using the API also offers greater control over how GeoJSON data is handled, processed, and utilized within CRM Analytics, catering to more advanced customization needs.
This method ensures that the consultant can fully utilize CRM Analytics' capabilities for creating highly customized geographic visualizations, thereby enhancing the analytical value of the dashboards.
NEW QUESTION # 94
A CRM Analytics consultant has enabled data sync manually in an org that uses dataflows/recipes. The client says that the dataflow/recipe fails each time it starts running.
What is causing the dataflow/recipe to fail?
- A. Dataflows/recipes with sfdcDigest nodes fail until sync has run for the first time.
- B. Dataflows/recipes with Augment nodes fail until sync has run for the first time.
- C. Dataflowsysrecipes with computeExpression nodes fail until syne has run for the first time.
Answer: A
NEW QUESTION # 95
Universal Containers (UC) builds three Einstein Discovery models in Salesforce to predict and maximize its revenue per customer. The modelsare for every region UC has a business: EMEA, AMER, and APAC.
How should a consultant help UC deploy the three Einstein models to Salesforce?
- A. Deploy the same mode! to all accounts and use an Apex trigger to segment the prediction.
- B. Segment the account data per region and deploy the appropriate model for each segment.
- C. Filter the account data per region and deploy the same model to all segments.
Answer: B
Explanation:
In deploying Einstein Discovery models that are tailored to different regions (EMEA, AMER, and APAC), the best approach is to segment the account data by region and apply the specific model designed for each segment. This method ensures the following:
* Relevance and Accuracy: Each model can be specialized to understand and predict based on regional dynamics, which may differ significantly across geographies in terms of market behavior, customer preferences, and economic conditions.
* Efficiency: Deploying region-specific models avoids the dilution of predictive power that might occur if a single model were used across all regions, which could lead to less accurate predictions.
* Scalability: This approach is scalable as UC can further refine each model as more regional data becomes available or as regional market conditions evolve.
NEW QUESTION # 96
Universal Containers intends to use a custom Salesforce big object in its org and visualize the data using CRM Analytics. As the number of rows to be synced is quite large, the CRM Analytics consultant is looking to set up an incremental sync with additional filters added as part of the data sync to improve performance.
What should the consultant keep in mind while implementing this?
- A. Custom big objects are NOT supported by CRM Analytics.
- B. Only SOSL queries can be used as data syne filters.
- C. Incremental data syne Is NOT supported for big objects.
Answer: C
NEW QUESTION # 97
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