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| Section | Objectives |
|---|
| Topic 1: Einstein Discovery | - Model building and predictions - Insights interpretation and recommendations
|
| Topic 2: Dashboard and App Development | - Lens creation and dashboard design - Interactive filters and user experience optimization
|
| Topic 3: Data Management and Preparation | - Data transformation and dataflows - Dataset creation and configuration in CRM Analytics
|
| Topic 4: Security and Access | - Row-level security and sharing rules - App and dataset permissions
|
| Topic 5: Data Integration and Connectivity | - Connecting external data sources - Data synchronization and refresh strategies
|
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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q114-Q119):
NEW QUESTION # 114
A CRM Analytics consultant is asked to make sure the new sales performance dashboard is accessible in the mobile app. They have created multiple mobile layouts for the same dashboard.
How is CRM Analytics expected to perform?
- A. If more than one layout Is eligible, the one with the most widgets is used.
- B. If more than one layout is eligible, the one with the most device properties set is used.
- C. If more than one layout is eligible, the one with the most global filters is used.
Answer: B
NEW QUESTION # 115
A customer has a dataset consisting of over 300 unique product names. They request a prediction model with the product names included.
Which action should the CRM Analytics consultant take?
- A. Run the model using the default variables in the Product object.
- B. Split the analysis into multiple models with each having fewer products.
- C. Use SKU numbers rather than product names to increase clarity.
Answer: B
NEW QUESTION # 116
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?
- A. Overwrite
- B. Update
- C. Append
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 # 117
Cloud Kicks (CK) wants to use CRM Analytics to analyze trends of its sales pipeline in order to accelerate the company's sales process. To do so, CK needs to know the average time an opportunity spends in each stage. The data can be found in the Opportunity History object, but the value is not pre- calculated in Salesforce, so a consultant recommends using a recipe to calculate it.
How should the consultant use a recipe to calculate the average time an opportunity spends in each stage?
- A. Flatten transformation with offset expressions to calculate the duration
- B. Custom transformation with a multiple row formula to calculate the duration
- C. An aggregate transformation with offset parameter to calculate the duration
Answer: B
NEW QUESTION # 118
A CRM Analytics consultant has prepared a CSV file to be uploaded to CRM Analytics. By mistake, one of the column headers is modified as random non-alphanumeric characters "*&**(&*(%", which went unnoticed prior to uploading the file.
What is the expected behavior of the uploaded CSV column?
- A. The columnheaderis prefixed with "X" upon upload.
- B. The column header Is set to *&**(&*(%.
- C. The column header is auto-updated to "Column" + column number.
Answer: A
Explanation:
When uploading CSV files into CRM Analytics, column headers must follow certain formatting rules.
Headers containing non-alphanumeric characters, such as "&**(&(%", will automatically be adjusted.
Specifically, if the column header starts with non-alphanumeric characters or contains such characters, CRM Analytics will prefix the header with "X" to ensure compatibility with internal naming conventions. This behavior ensures that the column can be referenced in the platform without causing errors or conflicts.
NEW QUESTION # 119
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