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Salesforce Analytics-Con-201 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Einstein Discovery	22%	- Deployment & Usage 1. Embed predictions in dashboards and Lightning pages 2. Interpret results and recommendations 3. Monitor and maintain model performance - Model Building & Configuration 1. Prepare and assess data for modeling 2. Train, evaluate, and refine models 3. Select prediction type: numeric, binary, multi-class
Topic 2: Data Layer	23%	- Data Sources & Integration 1. Define datasets and map Salesforce objects 2. Extract, load, and prepare data using Data Manager 3. Use Dataflows and Recipes for transformation - Data Management & Optimization 1. Implement data modeling and relationships 2. Optimize dataset performance 3. Resolve data sync and refresh issues
Topic 3: 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. Create lenses, steps, and visualizations 2. Implement bindings, filters, and interactions 3. Use SAQL for advanced queries
Topic 4: 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 5: Analytics Administration & Deployment	18%	- Implementation & Maintenance 1. Use Dashboard Inspector and Publisher 2. Monitor and optimize query performance 3. Manage versioning and deployment

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Salesforce Certified CRM Analytics and Einstein Discovery Consultant Sample Questions (Q68-Q73):

NEW QUESTION # 68
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 C
B. Option B
C. Option A

Answer: C

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 # 69
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 # 70
A CRM Analytics administrator is working on deploying a dashboard and a dataset from a developer sandbox to a full sandbox. They have deployed the dataset via change set and manually copy-pasted the dashboard JSON into the target org. However, they notice that the conditional formatting and the widget-specific number formats have been lost in the target environment.
What is causing this issue?

A. The recipe that generated the dataset also needs to be included as part of the package.
B. Analytics Dashboard XMD was NOT included as part of the deployment package.
C. Analytics Dataset XMD was NOT included as part of the deployment package,

Answer: C

Explanation:
When deploying a dataset and dashboard between environments in CRM Analytics, it's essential to include theExtended Metadata (XMD)file, which controls aspects such as conditional formatting and number formatting. In this case, the administrator manually copied the dashboard JSON but did not deploy the Analytics Dataset XMD, which leads to the loss of conditional formatting and widget-specific number formats in the target environment. Including the XMD ensures that all formatting and metadata are transferred correctly.

NEW QUESTION # 71
The marketing team at Cloud Kicks has five dashboards in an app. Four widgets are replicas of each other in three of the dashboards.
What is the best way to maintain these widgets?

A. Create/Edit a lens and add each dashboard.
B. Create/Edit a component for the widgets.
C. Create/Edit the widgets individually on each dashboard.

Answer: B

Explanation:
To maintain consistency and ease of updates across multiple dashboards, creating or editing a component for the widgets is the most effective method. This approach:
Efficiency in Updates: Allows changes to be made in one place, which automatically propagates to all instances where the component is used across dashboards.
Consistency: Ensures uniformity in the appearance and functionality of the widgets across different dashboards.
Simplicity: Reduces the need for redundant work, where each widget would otherwise need to be updated individually.

NEW QUESTION # 72

Which timeseries statement will fix the query?

A. q = timeseries q generate 'sum_Sales' as 'Forecasted_Sales' with (dateCols=('Date_Quarter',
'Date_Month', "Q-M"), partition='Region', ignoreLast=true);
B. q = timeserles q generate 'sum_Sales' as 'Forecasted_Sales' with (length=12,dateCols=("Date_Year',
'Date_Month', "Y-M"), partition='Region');
C. q= timeseries q generate 'sum_Sales' as 'Forecasted_Sales' with (dateCols=('Date_Year', 'Date Quarter', "Y-Q"), partition='Region', seasonality=4);

Answer: B

NEW QUESTION # 73
......

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