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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionWeightObjectives
Data Layer25%- Implement and configure the right data transformations
  • 1. Use Data Prep actions
  • 2. Identify and resolve data sync issues
- Identify the right data sources and data flows for CRM Analytics
  • 1. Describe how Salesforce objects map to CRM Analytics
  • 2. Define datasets
  • 3. Describe use cases for Data Prep (Dataflows and Recipes)
Security10%- Determine security and sharing settings
  • 1. Describe how Salesforce security is applied in CRM Analytics
  • 2. Implement row-level security
Analytics Dashboard Design20%- Design and build CRM Analytics dashboards
  • 1. Use Lenses and Dashboards
  • 2. Describe the use cases for Visualforce and Lightning components
  • 3. Apply design best practices
Analytics Dashboard Configuration25%- Configure dashboards
  • 1. Apply query filters
  • 2. Set up dynamic dashboards
  • 3. Configure bindings
Einstein Discovery20%- Describe Einstein Discovery concepts
  • 1. Interpret model results
  • 2. Explain the model building process
  • 3. Identify the use cases for Einstein Discovery
- Implement Einstein Discovery
  • 1. Configure and deploy Einstein Discovery models
  • 2. Integrate predictions into CRM Analytics dashboards

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q39-Q44):

NEW QUESTION # 39
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?

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 # 40
Universal Containers' CRM Analytics team is building a dashboard with two widgets.
1. List widget associated to the query "Type_2" and grouped by the dimension "Type" (multi-selection)
2. Donut chart widget associated to the query "Step_pie_3" and grouped by the dimension "Type" The team wants to use bindings/interactions so any selection in the List widget will filter the Donut chart. The queries use different datasets, and users should be able to choose more than one Type (multi-selection).
What is the right syntax for the binding/interaction?

Answer: B

Explanation:
For the given requirement where a selection in a list widget needs to filter data displayed on a donut chart, and considering the list allows for multi-selection of the 'Type', the correct binding/interaction would be to use a syntax that captures the multi-select aspect and passes it appropriately. The right syntax, as indicated in Option A, looks like this:
"{{column(Type_2.selection, [\"Type\"]).asObject()}}"
This syntax ensures:
* Multi-selection: The column() function in combination with .asObject() ensures that multiple selected values from the 'Type_2' query can be passed as an object, which the donut chart can utilize to filter its content.
* Correct Data Type Handling: By using .asObject(), the binding ensures the data passed between widgets maintains the correct structure expected by the CRM Analytics dashboard, thereby ensuring accurate filtering.


NEW QUESTION # 41
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?

Answer: A

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 # 42
Universal Containers plans to upload target data from an external tool to CRM Analytics so it can calculate the sales team target attainments.
The target data changes every month, so the datasets need to be updated on a monthly basis. The target data is a CSV file that contains the Salesforce ID of the sales rep, the target amount, and the month of the target. For each sales rep, the file contains a target for every month of the current year as well as all previous years.
Based on this information, which operation should a consultant use with the Analytics External Data API to upload the file?

Answer: A

Explanation:
For uploading target data that changes on a monthly basis and includes historical data (previous years' targets), the appropriate operation is "Overwrite." This ensures that each time the CSV file is uploaded, the existing data in the dataset is replaced with the new data. This is critical because the target data includes both current and historical data, and using "Overwrite" will update the entire dataset while maintaining historical accuracy.
"Append" would add new data without replacing the old records, leading to duplication, and "Update" is not suitable for completely replacing data in this context.


NEW QUESTION # 43
Universal Containers (UC) uses a Microsoft Azure SQL Data Warehouse to gather information about sales reps' objectives. UC wants to use CRM Analytics to gain insights from this data and automatically load it into a CRM Analytics dataset daily. The data also needs to be transformed and merged with data from the company's org.
Which CRM Analytics user interface features should be used to complete these requirements?

Answer: A


NEW QUESTION # 44
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