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| Section | Weight | Objectives |
|---|---|---|
| Data Layer | 25% | - Identify the right data sources and data flows for CRM Analytics
|
| Analytics Dashboard Design | 20% | - Design and build CRM Analytics dashboards
|
| Analytics Dashboard Configuration | 25% | - Configure dashboards
|
| Einstein Discovery | 20% | - Describe Einstein Discovery concepts
|
| Security | 10% | - Determine security and sharing settings
|
>> Analytics-Con-201 New Study Notes <<
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NEW QUESTION # 18
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: C
NEW QUESTION # 19
The sales team at Cloud Kicks is requesting that datasets for their dashboards be refreshed every hour. The CRM Analytics consultant investigates if this is possible and finds that the dashboards use five datasets created from two recipes. The first recipe takes 43 minutes to run and the second recipe takes 25 minutes to run.
Which consideration should the consultant keep in mind?
Answer: B
Explanation:
In CRM Analytics, recipes are used to prepare and combine data for datasets. The total duration of the recipe runtime is an important consideration when scheduling dataset refreshes. In this case, the combined runtime for both recipes (43 minutes + 25 minutes = 68 minutes) exceeds 1 hour. Since dataset refreshes cannot be scheduled more frequently than the total recipe runtime, it would beimpossible to refresh the datasets every hour. This limitation must be considered when managing dataset refresh schedules.
Reference: Recipe runtime limits and considerations for scheduling refreshes are discussed in the CRM Analytics documentation related to recipes and dataflow optimizations.
NEW QUESTION # 20
CRM Analytics uses permissions of the Integration User to extract data from Salesforce objects and fields when a dataflow/recipe job runs.
Why should a consultant be cautious while syncing objects and fields containing sensitive data?
Answer: C
NEW QUESTION # 21
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 # 22
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: C
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 # 23
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