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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Dashboard Design & Development	25%	- Design Principles 1. Design for mobile and Lightning compatibility 2. Apply best practices for usability and performance - Build & Configure Dashboards 1. Implement bindings, filters, and interactions 2. Use SAQL for advanced queries 3. Create lenses, steps, and visualizations
Topic 2: Security & Access	12%	- Sharing & Permissions 1. Configure app, dataset, and field-level security 2. Implement row-level security and inheritance 3. Manage user and group access
Topic 3: Einstein Discovery	22%	- Model Building & Configuration 1. Train, evaluate, and refine models 2. Select prediction type: numeric, binary, multi-class 3. Prepare and assess data for modeling - Deployment & Usage 1. Monitor and maintain model performance 2. Interpret results and recommendations 3. Embed predictions in dashboards and Lightning pages
Topic 4: Data Layer	23%	- Data Management & Optimization 1. Optimize dataset performance 2. Implement data modeling and relationships 3. Resolve data sync and refresh issues - Data Sources & Integration 1. Use Dataflows and Recipes for transformation 2. Extract, load, and prepare data using Data Manager 3. Define datasets and map Salesforce objects
Topic 5: Analytics Administration & Deployment	18%	- Implementation & Maintenance 1. Use Dashboard Inspector and Publisher 2. Manage versioning and deployment 3. Monitor and optimize query performance

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

NEW QUESTION # 72
What is a benefit of introducing a second local connector?

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

Answer: C

Explanation:
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.

NEW QUESTION # 73
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. Use "Connect Data Sources" to create a mapping of the two fields from the two datasets.
C. Set up a result and selection based interaction for each query.

Answer: C

NEW QUESTION # 74
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 @ timeseries statement specifying Account Name as the partition and Y-M-D as the Date Cols
B. An SAQL query with a timeseries statement specifying Account Name as the partition and Y-M-W 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: B

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 # 75
Cloud Kicks has a dashboard that displays accounts and opportunities data in a table that contains actions to open the records in Salesforce. Since the company has allowed several accounts to be created with the same names, when users try to perform actions, they are prompted with only a record ID to select, leaving the users confused and unable to act.
How should the CRM Analytics consultant solve this problem?

A. Discuss with the stakeholders If the action Is really necessary for the table.
B. Ask the admin to start applying duplicate rules based on the account's Name field.
C. Insert more fields in the dataset action "Display Fields" so the users know which account they are acting on.

Answer: C

NEW QUESTION # 76
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?

A. Option B
B. Option A
C. Option C

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 # 77
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