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Salesforce CRM-Analytics-and-Einstein-Discovery-Consultant Exam Syllabus Topics:

Topic	Details
Topic 1	Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.
Topic 2	Admin Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync dataflows recipe limits.
Topic 3	Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.
Topic 4	Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q56-Q61):

NEW QUESTION # 56
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?

A. substr()
B. replace()
C. coalesce()

Answer: C

NEW QUESTION # 57
An insurance company has many Einstein Analytics dashboards that show the influence of weather, such as atmospheric temperature, on customer cases. A service agent commented that it is sometimes difficult to determine, by looking at a dashboard, whether the temperature data is reported in degrees Fahrenheit or in degrees Celsius.
How can a dashboard designer ensure the temperature data is easier to interpret on the dashboards?

A. Customize the number format in the number widget properties of the dashboard.
B. In Explorer, go to the Fields menu and then customize the number format of the measure.
C. Add a text widget to the dashboard to indicate Fahrenheit or Celsius.
D. Use the XMD node in the dataflow to customize the number format of the field.

Answer: C

NEW QUESTION # 58
Which three things can be done with the tableau CRM Dashboard Inspector?
Choose 3 answers

A. Automatically remove bottlenecks to make queries run faster.
B. View the total time required to run all queries.
C. Get a list of recommendations on how to improve the performance of the dashboard.
D. View all queries and the time it took to run each one.
E. See the final query for each query along with query results.

Answer: C,D,E

NEW QUESTION # 59
What kind of org should you use for checking challenges when you do Trailhead modules about Analytics?

A. A higher education org, because analytics requires advanced math
B. A trial org, because you don't need to save anything
C. A Developer Edition org, because it's a free, safe environment where you can try things out
D. An enterprise org, because that type of org is typically used by large companies

Answer: C

NEW QUESTION # 60
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?

A. Root Mean Square Error, Minimum Square Error
B. Area Under Curve, R2 (R-squared)
C. Area Under Curve, Confusion Matrix

Answer: A

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 # 61
......

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CRM-Analytics-and-Einstein-Discovery-Consultant Pass-King Torrent - CRM-Analytics-and-Einstein-Discovery-Consultant Actual Exam & CRM-Analytics-and-Einstein-Discovery-Consultant Exam Torrent

Salesforce CRM-Analytics-and-Einstein-Discovery-Consultant Exam Syllabus Topics:

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q56-Q61):

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