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Salesforce Analytics-Con-201 Exam Syllabus Topics:

SectionObjectives
Topic 1: Einstein Discovery- Insights interpretation and recommendations
- Model building and predictions
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- App and dataset permissions
- Row-level security and sharing rules
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 (Q83-Q88):

NEW QUESTION # 83
A model created with a GLM algorithm produced unsatisfactory results.
When re-running the model, which type of algorithm should the consultant use to improve the results?

Answer: A


NEW QUESTION # 84
Exhibit.

Universal Containers has a dashboard for sales managers to visualize the Year Over Year (YoY) growth of their customers. The formula used is:
YoY = [(This Year - Last Year) / Last Year] %
Based on the graphic, when there is not an account in the Last Year column, the YoY Growth shows null results. The sales managers want to replace it with 100% value.
What is the correct function to use?

Answer: B


NEW QUESTION # 85
The below image shows a numeric outcome being deployed (Regression).

Which metric is used to calculate the performance of the model in production, specifically in the Model Manager?
The below image shows a numeric outcome being deployed (Regression).
Which metric is used to calculate the performance of the model in production, specifically in the Model Manager?

Answer: B

Explanation:
In the context of a regression model being deployed, the performance metrics used to evaluate its effectiveness in production typically include:
* Root Mean Square Error (RMSE): This metric provides a measure of the average magnitude of the errors between predicted values by the model and the actual values, giving a sense of how accurately the model predicts the outcome.
* Minimum Square Error: While less commonly referenced as "Minimum Square Error", metrics like Mean Squared Error (MSE) are often used to quantify the average of the squares of the errors- essentially, the average squared difference between the estimated values and what is estimated.
These metrics are crucial for assessing the performance of regression models in CRM Analytics, as they directly reflect the accuracy and reliability of the model's predictions in real-world applications.


NEW QUESTION # 86
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: B

Explanation:
Reference:CRM Analytics Connectors and Dataflows


NEW QUESTION # 87
Universal Containers builds a new sales dashboard and wants to makesure account managers can access the dashboard while traveling.
What should the consultant consider doing in this process?

Answer: B


NEW QUESTION # 88
......

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