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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Einstein Discovery	20%	- Implement Einstein Discovery 1. Configure and deploy Einstein Discovery models 2. Integrate predictions into CRM Analytics dashboards - Describe Einstein Discovery concepts 1. Explain the model building process 2. Identify the use cases for Einstein Discovery 3. Interpret model results
Analytics Dashboard Design	20%	- Design and build CRM Analytics dashboards 1. Use Lenses and Dashboards 2. Describe the use cases for Visualforce and Lightning components 3. Apply design best practices
Security	10%	- Determine security and sharing settings 1. Describe how Salesforce security is applied in CRM Analytics 2. Implement row-level security
Data Layer	25%	- Implement and configure the right data transformations 1. Identify and resolve data sync issues 2. Use Data Prep actions - Identify the right data sources and data flows for CRM Analytics 1. Describe use cases for Data Prep (Dataflows and Recipes) 2. Define datasets 3. Describe how Salesforce objects map to CRM Analytics
Analytics Dashboard Configuration	25%	- Configure dashboards 1. Configure bindings 2. Apply query filters 3. Set up dynamic dashboards

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q72-Q77):

NEW QUESTION # 72
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?

A. Support Vector Machines
B. XGBoost
C. K-Nearest Neighbors

Answer: B

NEW QUESTION # 73
Acompany wants to create a timeline chart to visualize the evolution of its Closed Won opportunities.

What are the required parameters to build a lens that displays output similar to the image shown?

A. 1 measure, 1 grouping by a date field, and either 0-1 groupings groupings by a dimensionif trellis is disabled, or 0-2groupings if trellis is enabled
B. 1 measure, 1-2 groupings if trellis is disabled, or 1-4 groupings if trellis is enabled
C. 1 measure, 0 groupings if trellis Is disabled, or 0-2 groupings If trellis is enabled

Answer: A

Explanation:
To create a timeline chart similar to the one shown, the following parameters are typically required:
* 1 Measure: This could be the count of Closed Won opportunities or any other relevant metric that needs to be tracked over time.
* 1 Grouping by a Date Field: This is essential to plot the timeline effectively. The date field would typically be the close date of the opportunities.
* Additional Groupings: Depending on the complexity and the detail needed, additional groupings can be added. For example, grouping by region or product line can provide more insights into the timeline. If trellis is used, it allows for the creation of multiple smaller charts within the main chart, each representing a slice of data based on the additional groupings.
This setup helps visualize the evolution of Closed Won opportunities over time, making it easy to spot trends, seasonal patterns, or other relevant insights.

NEW QUESTION # 74
A CRM Analytics consultant is performing column profiling on dimension column in a recipe. Newly-added rows are not being considered in the Results tab of theprofile even though a sync wasrun for that specific object.
What is causing the issue?

A. Column profiling Is not applicable on a dimension column in a recipe.
B. The sample does not include changes to the connected object data within the last 24 hours.
C. Sync operation has not run properly with the new dimension column in the recipe.

Answer: B

NEW QUESTION # 75
AW Computing will start using Tableau Online to report on some of its Salesforce data to users who do NOT have an SFDC license.
What is the first step the CRM Analytics consultant should take?

A. Use MuleSoft to generate an API ta connect and push data from SFDC to Tableau.
B. Enable the Tableau output connection in the Analytics settings.
C. Select the output connection in the "write to" option of the recipe.

Answer: B

NEW QUESTION # 76
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 # 77
......

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