Analytics-Con-201최고품질덤프문제모음집 & Analytics-Con-201높은통과율공부자료

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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Objectives
Topic 1: Einstein Discovery	- Insights interpretation and recommendations - Model building and predictions
Topic 2: Security and Access	- Row-level security and sharing rules - App and dataset permissions
Topic 3: Data Integration and Connectivity	- Data synchronization and refresh strategies - Connecting external data sources
Topic 4: Data Management and Preparation	- Data transformation and dataflows - Dataset creation and configuration in CRM Analytics
Topic 5: Dashboard and App Development	- Interactive filters and user experience optimization - Lens creation and dashboard design

>> Analytics-Con-201최고품질 덤프문제모음집 <<

Analytics-Con-201높은 통과율 공부자료 - Analytics-Con-201퍼펙트 최신 덤프공부

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최신 Salesforce Consultant Analytics-Con-201 무료샘플문제 (Q15-Q20):

질문 # 15
After the initial creation of a model, the first model insight explains
93% of the variation of the outcome variable. This is unusually high.
What is the most likely reason for this?

A. The model contains too many outlier values.
B. The dataset contains multiple dominant values.
C. The outcome variable may be causing data leakage.

정답：C

질문 # 16
What is a benefit of introducing a second local connector?

A. Better maintenance by having a connector per recipe
B. Better performance by syncing data according to the refresh necessities
C. Better deployment management between sandboxes and production environment

정답：B

설명：
Introducing a second local connector in CRM Analytics can improve performance by enabling more granular control over data syncs. By having a separate connector, different datasets or recipes can be synchronized independently based on specific refresh needs, reducing load and improving overall performance. This approach helps optimize data flow operations, especially in large-scale deployments with varying data refresh requirements.

질문 # 17
consultant is reviewing a model that is set to maximize the daily sales quantity of consumer products in stores, and they see this recommendation.

Which action should the consultant take?

A. Ignore alert; the explanation of variation is only 35%, which is below 50%,
B. Remove the Store field from the model definition, because that is the recommended action.
C. Verifyclient expectations that Store is a strong predictor for daily sales quantity.

정답：C

설명：
Upon reviewing the data model and noticing the high correlation alert between 'Store' and daily sales quantity, the appropriate action is to verify with the client their expectations regarding the influence of the Store field on daily sales. Here's the rationale:
* Understanding the Role of 'Store' in the Model: Before making any changes to the model, it's crucial to understand whether the 'Store' field is expected to be a strong predictor based on the business context. If the client expects that different stores inherently have different sales volumes due to factors like location, size, or customer base, this correlation may be both meaningful and desired.
* Potential Data Leakage: High correlation warnings can sometimes indicate data leakage, where a predictor (like 'Store') might inadvertently include information about the outcome variable (daily sales quantity). It's essential to verify whether this correlation makes sense logically or if it's skewing the model predictions.
* Client Consultation: Consulting with the client helps ensure that any modeling decisions align with their business knowledge and expectations. It's about validating the model against real-world expectations and ensuring it remains a useful tool for decision-making.
By taking these steps, the consultant not only adheres to best practices in data science by validating model inputs and their implications but also ensures that the model aligns with the client's business strategies and operational realities.

질문 # 18
Universal Containers' CRM Analytics team is building a dashboard with two widgets, and the queries use different datasets.
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 "Query_pie_3" and grouped by the dimension "Type" The team wants any selection in the List widget to filter the Donut chart and vice versa. Users should be able to choose more than one Type (multi-selection).
What is the recommended way to accomplish the required filtering?

A. Create a selection based Interaction and apply It to the query of "Query ple 3".
B. Set up a result and selection based interaction for each query.
C. Use "Connect Data Sources" to create a mapping of the two fields from the two datasets.

정답：B

질문 # 19
Universal Containers is setting up a Sales Analytics app to track the sales performance across all regions. The role hierarchy is well-structured with separate branches for various global regions.
Viewer access has been provided to the regional sales reps based on the following roles.
* Regional Sales - APAC
* Regional Sales - EMEA
* Regional Sales - LATAM
* Regional Sales - NA
The CRM Analytics project team receives a request to extend Editor
access to the app to 20 'Superusers' across all regions.
What is the optimal solution?

A. Create a new sharing rule for these users and assign it the Editor app access.
B. Create a new public group with these users and assign it the Editor app access.
C. Create new roles for these users and assign them the Editor app access.

정답：B

질문 # 20
......

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