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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Dashboard Design & Development	25%	- Design Principles 1. Apply best practices for usability and performance 2. Design for mobile and Lightning compatibility - Build & Configure Dashboards 1. Implement bindings, filters, and interactions 2. Create lenses, steps, and visualizations 3. Use SAQL for advanced queries
Einstein Discovery	22%	- Model Building & Configuration 1. Prepare and assess data for modeling 2. Select prediction type: numeric, binary, multi-class 3. Train, evaluate, and refine models - Deployment & Usage 1. Monitor and maintain model performance 2. Interpret results and recommendations 3. Embed predictions in dashboards and Lightning pages
Security & Access	12%	- Sharing & Permissions 1. Manage user and group access 2. Configure app, dataset, and field-level security 3. Implement row-level security and inheritance
Data Layer	23%	- Data Sources & Integration 1. Extract, load, and prepare data using Data Manager 2. Define datasets and map Salesforce objects 3. Use Dataflows and Recipes for transformation - Data Management & Optimization 1. Resolve data sync and refresh issues 2. Optimize dataset performance 3. Implement data modeling and relationships
Analytics Administration & Deployment	18%	- Implementation & Maintenance 1. Manage versioning and deployment 2. Use Dashboard Inspector and Publisher 3. Monitor and optimize query performance

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q43-Q48):

NEW QUESTION # 43
Cloud Kicks (CK) has a dashboard in CRM Analytics with forecasting data. One widget is a compare table using the timeseries function showing the quarterly forecast. However, CK is interested in enhancing the dashboard with a weekly forecast per customer.
How should CK achieve this?

A. An SAQL query with a timeseries statement specifying Account Name as the partition and Y-M-W as the Date Cols
B. An SAQL query with @ timeseries statement specifying Account Name as the partition and Y-M-D as the Date Cols
C. An SAQL query with a timeseries statement specifying Opportunity Name as the partition and Y-M-W as the Date Cols

Answer: A

Explanation:
To create a weekly forecast per customer, anSAQL (Salesforce Analytics Query Language)query can be used.
The timeseries function generates forecast data based on a specified date range. In this case, the forecast is customer-specific, meaning the partition should be based onAccount Nameto ensure that the forecast is generated for each customer. The date column (Date Cols) should be set to Y-M-W to aggregate the forecast data on a weekly basis.
Reference: The use ofSAQL and timeseries functionsis covered in theWave Analytics ExplorerandAdvanced SAQLmodules, where partitioning and date-based aggregations are explained in detail.

NEW QUESTION # 44
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?

A. The total duration of the recipe runtimes can exceed the limit of 1 hour.
B. The number of concurrent recipe runs can exceed the limit of two in a 24-hour rolling period.
C. The number of concurrent recipe run limits that are associated with the org.

Answer: A

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.

NEW QUESTION # 45
What can a consultant accomplish in the Predictions page of a model?

A. If it is decided to follow some of the Einstein Recommendations for model improvement, see what the new model metrics would be.
B. Estimate the impacted business value of using Einstein Discovery.
C. Create predicted outcome value by manually selecting values for some of the predictor fields.

Answer: C

Explanation:
In the Predictions page of a model within CRM Analytics (formerly Einstein Discovery), users have the capability to interact with the model to see how different input values affect predictions. Here's a detailed look at what can be accomplished:
* Manual Input of Predictor Values: Users can manually input or change values for predictor fields to see how these changes alter the predicted outcomes. This is especially useful for testing hypothetical scenarios and understanding how sensitive the model is to various inputs.
* Real-Time Interaction: This functionality provides a hands-on way to explore the model's behavior, offering immediate feedback on how input variations impact predictions, which can help in refining the model or in training users on its application.
* Scenario Analysis: By adjusting predictor values, users can conduct scenario analyses, which are crucial for strategic planning and decision-making.

NEW QUESTION # 46
A CRM Analytics consultant is asked to help a company report on its sales activity. The company wants to train some users to create dashboards. The company also wants one other specific team to be able to use the dashboards.
What should the consultant do to address these requirements?

A. configure a permission set license assignment with two different levels of access.
B. Clone the existing permission set with different system permissions.
C. Use a permission set license with two different levels of access.

Answer: A

Explanation:
To meet the requirement of training some users to create dashboards while giving another team access to use (but not modify) those dashboards, the best approach is to configure a permission set license assignment with two different levels of access. You can assign specific permissions for dashboard creation to one group of users and viewing permissions to the other. This ensures the appropriate level of access based on the role without the need for duplicating permission sets or licenses unnecessarily.
Reference: The role of permission sets and permission set licenses in managing different levels of access is outlined inSalesforce CRM Analyticsuser management and security documentation

NEW QUESTION # 47
Universal Containers (UC) builds three Einstein Discovery models in Salesforce to predict and maximize its revenue per customer. The modelsare for every region UC has a business: EMEA, AMER, and APAC.
How should a consultant help UC deploy the three Einstein models to Salesforce?

A. Filter the account data per region and deploy the same model to all segments.
B. Segment the account data per region and deploy the appropriate model for each segment.
C. Deploy the same mode! to all accounts and use an Apex trigger to segment the prediction.

Answer: B

Explanation:
In deploying Einstein Discovery models that are tailored to different regions (EMEA, AMER, and APAC), the best approach is to segment the account data by region and apply the specific model designed for each segment. This method ensures the following:
* Relevance and Accuracy: Each model can be specialized to understand and predict based on regional dynamics, which may differ significantly across geographies in terms of market behavior, customer preferences, and economic conditions.
* Efficiency: Deploying region-specific models avoids the dilution of predictive power that might occur if a single model were used across all regions, which could lead to less accurate predictions.
* Scalability: This approach is scalable as UC can further refine each model as more regional data becomes available or as regional market conditions evolve.

NEW QUESTION # 48
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